{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 量化评估"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 年化收益率\n",
    "\n",
    "年化收益率是把当前收益率（日收益率、周收益率、月收益率）换算成年收益率来计算的，是一种理论收益率，并不是真正的已取得的收益率。因为年化收益率是变动的，所以年收益率不一定和年化收益率相同。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "总收益率：$$R=\\frac{P_T-P_t}{P_t}$$\n",
    "其中，$P_T$是期末卖出时的价格，$P_t$是期初买入时的价格。  \n",
    "\n",
    "年化收益率：$$R_p=(1+R)^{\\frac{m}{n}}-1$$\n",
    "其中，R是期间总收益率，m是与n（可以是天数、周数、月数）相对应的计算周期，根据计算惯例，m=250、52、12分别指代日、周、月向年化的转换。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最大回撤"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在选定周期内任一历史时点往后推，产品净值走到最低点时的收益率回撤幅度的最大值。最大回撤用来描述买入产品后可能出现的最糟糕的情况。最大回撤是一个重要的风险指标，对于对冲基金和数量化策略交易，该指标比波动率还重要。\n",
    "P为某一天的净值，i为某一天，j为i后的某一天，Pi为第i天的产品净值，Pj则是Pi后面某一天的净值\n",
    "则该基金的最大回撤率计算如下：\n",
    "$$Max\\_drawdown=\\frac{max(P_i-P_j)}{P_i}$$\n",
    "即通过对每一个净值进行回撤率求值，然后找出最大的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Beta: 贝塔系数\n",
    "\n",
    "*相当于业绩评价基准收益的总体波动性\n",
    "$$beta=\\beta_p=\\frac{Cov(P_i,P_m)}{Var_m}$$\n",
    "\n",
    "*衡量策略的系统性风险：\n",
    "如果Beta为1，策略和市场（参照沪深300指数）同进退\n",
    "如果Beta为1.1，市场上涨10%时，策略上涨11%；市场下滑10%时，策略下滑11%。\n",
    "如果Beta为0.9，市场上涨10%时，策略上涨9%；市场下滑10%时，策略下滑9%。\n",
    " \n",
    "那么问题来了, Beta值到底是大好还是小好呢？\n",
    "这得具体问题具体分析，如果是牛市，股市兴兴向荣，个股、大盘狂涨，那就要选择Beta值大的策略；\n",
    "如果是熊市，经济下行压力大，就应该选择Beta值小的策略，这样就可以比较好的控制风险，确保资金的安全。\n",
    "\n",
    "### Alpha：阿尔法系数\n",
    "*实际收益和按照Beta系数计算的期望收益之间的差额。\n",
    "*代表策略多大程度上跑赢了预期的收益率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### beta和alpha的估计\n",
    "这里的beta和alpha系数都来自资本资产定价模型，先来看看CAPM：\n",
    "$$E(r_i)=r_f+\\beta (E(r_m)-r_f)$$\n",
    "$E(r_i)$是股票i的预期收益率，$r_f$是无风险利率，$E(r_m)$是市场指数收益率；\n",
    "$\\beta$系数是系统性风险，在评估股市波动风险与投资机会的方法中，常用来衡量结构性与系统性风险，可以简单理解为个股波动相对大盘波动的偏离程度。CAPM的计量模型可以表示为：\n",
    "$$r_i=\\alpha+\\beta r_m+\\varepsilon$$\n",
    "$\\alpha$可以理解为超额收益率，$\\varepsilon$是随机扰动，可以理解为个体风险。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 夏普比率\n",
    "\n",
    "*代表投资人每多承担一分风险，可以拿到几分报酬；\n",
    "   ---单位风险所获得的超额回报率\n",
    "*该比率越高，策略承担单位风险得到的超额回报率越高。\n",
    " 所以说夏普比率是越高越好滴..\n",
    " \n",
    " $$Sharpe\\_ratio= \\frac{R_p-R_f}{\\sigma_p}$$\n",
    " 其中，$R_p$为年化收益率， $R_f$ 是无风险收益率，$\\sigma_p$为年化波动率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 信息比率\n",
    "$$Information\\_ratio=\\frac{R_p-R_m}{\\sigma_t} $$\n",
    "其中，$R_p$为年化收益率， $R_f$ 为基准年化收益率（如沪深300指数），$\\sigma_t$为策略与基准每日收益率差值的年化标准差"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Python计算实例\n",
    "使用tushare获取交易数据，考虑最简单的策略：买入持有！分别计算期间总收益率，年化收益率，最大回撤，beta、alpha系数，夏普比率和信息比率。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#先引入后面可能用到的包（package）\n",
    "import pandas as pd  \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline   \n",
    "\n",
    "#正常显示画图时出现的中文和负号\n",
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif']=['SimHei']\n",
    "mpl.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "### 获取数据：tushare开源库（确认已安装好：pip install tushare）\n",
    "import tushare as ts\n",
    "#起始和结束日期可以自行输入，否则使用默认\n",
    "def get_data(code,start_date=\"2009-01-01\", end_date=\"2019-01-18\"):\n",
    "    df = ts.get_k_data(code, start=start_date, end=end_date)\n",
    "    df.index=pd.to_datetime(df.date)\n",
    "    return df.close\n",
    "#返回收盘价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#以上证综指、贵州茅台、工商银行、中国平安为例\n",
    "stocks={'sh':'上证综指','600519':'贵州茅台',\n",
    "        '601398':'工商银行','601318':'中国平安'}\n",
    "#获取上述股票（指数）的每日前复权收盘价\n",
    "df=pd.DataFrame()\n",
    "for code,name in stocks.items():\n",
    "    df[name]=get_data(code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>上证综指</th>\n",
       "      <th>贵州茅台</th>\n",
       "      <th>工商银行</th>\n",
       "      <th>中国平安</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-05</th>\n",
       "      <td>1880.72</td>\n",
       "      <td>68.615</td>\n",
       "      <td>2.178</td>\n",
       "      <td>12.513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-06</th>\n",
       "      <td>1937.15</td>\n",
       "      <td>68.824</td>\n",
       "      <td>2.239</td>\n",
       "      <td>12.952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-07</th>\n",
       "      <td>1924.01</td>\n",
       "      <td>67.609</td>\n",
       "      <td>2.190</td>\n",
       "      <td>12.956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-08</th>\n",
       "      <td>1878.18</td>\n",
       "      <td>68.710</td>\n",
       "      <td>2.142</td>\n",
       "      <td>12.292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-09</th>\n",
       "      <td>1904.86</td>\n",
       "      <td>67.925</td>\n",
       "      <td>2.166</td>\n",
       "      <td>12.323</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               上证综指    贵州茅台   工商银行    中国平安\n",
       "date                                      \n",
       "2009-01-05  1880.72  68.615  2.178  12.513\n",
       "2009-01-06  1937.15  68.824  2.239  12.952\n",
       "2009-01-07  1924.01  67.609  2.190  12.956\n",
       "2009-01-08  1878.18  68.710  2.142  12.292\n",
       "2009-01-09  1904.86  67.925  2.166  12.323"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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/Vd+bKtbahG1Y0qEj/b5ERERERLAWQgHIyE5fDCvmwgtnwqAj4NI5u+4vLdGohKnLDrttrHQnniIiIiIiHc4/b4J7d4Oa6vS8/x83wrTz3XFFSXpikDqUfIqIiIiISOoEKmCBt8DPJ1PTE8OCpyCwwx1vW52eGKQOJZ8iIiIiIpI6m/4XO968LH1xRNiQGwYsaafkM41ae76tiIiIiEibq9wWOw7uTF8c8QLl6Y5A6OLJ57Zt23j77bd5++23uemmm7jhhhui5+vWrYv2++Uvf8msWbMSPhsKhTjqqKMAKCoqYsGCBbz++uuMGTOGRYsW8d577zF8+HAWLVrEwoULWb9+fcLn33//fU4//XQloCIiIiLSuYSDseNABVRuhw2ftuH7k2xf+MU/ofjLtotBkurSyefHH3/Ms88+S01NDT6fD5/PR01NDe+88w5vvPFGtJ8xhuxst1LXscceC4Df7yc31y3fvGbNGj744AOWLFlCeXk5ixYtYvHixVRWVrJo0SIWLFjAhg0bos/bvn0711xzDb/4xS8wxnDdddexbFk7GJIgIiIiItJS4ZrYcbACXpgETx3TdkNfk22t8tqP4IkjoGxD3XvSZrrsPp8A3bt3Z9WqVdx7771s2rQJay0LFizAWsu1114b7WeMia56261bt4TrAEcddRQFBQVceeWVVFdX88Ybb2CtpaqqildffZWpU6fSr18/wFVbzz33XB544AFGjBgBwCWXXMJ5553HzJkzo3t+ioiIiIh0SKG4yueKt6GmyrveRluvRJLPEd+D5XNg5+bYvW0rofuA1o9Bkkp/8vnPm2HjktQ+s//BcMoDDXaZM2cOH374IWeeeSbgqpfWWoYMGQLAl19+ycyZM5kyZQoTJkzgjTfeoKysDICf//zn/OxnP0t43sEHH8w777zD7NmzKSkp4dBDD+XGG2/kRz/6Ebvttlu032mnncaqVau4//77+dWvfhWtuA4bNoxTTz2Vd999l969e6fytyEiIiIi0nbCIdd23x3KYlPZCFa0bfI5dByM+iE8MzF2L9BO5qB2UelPPtNk4sSJHHHEEZxzzjkJ15cuXQrAU089xdChQ3nsscew1jJ69GimT58OwKhRo5gyZUr0M/Pnz+eWW27B7/cTDod59913McZw8MEH89hjj/HYY49x3333MWbMGJ555hkKCwvp169fnT1E582bR8+ePVv5m4uIiIiItKLInM/sgsTrwSrIbYP3B7zkMzMXcrrXuqeFh9Ip/cnnLiqUrckYQ0ZGBrNmzWLmzJnst99+DB8+nB/84AdUV1ezatUqDjvsMDZt2sQpp5xCOBzmxRdf5LTTTosmogBjxoxhzpw5+P1+Xn75ZQoKCli/fj0LFy7EWsvYsWM5+OCDASguLuaYY46JVlgj1q5dy5/+9Cf8fn+b/g5ERERERFIqMuczs1ammWwuZmuIvCerG2TXSj6r45LPHZugugz67NM2cUnXXnAoGAySm5tLKBTikUceYfPmzXzxxRccfPDB5OTksNdee/HLX/6Szz//nH333ZfvfOc7gFtsKHIM4PP5CAaD3HbbbcyePZvp06dHk0hjDPPnzycvLw+ArKwsJk2axKJFixJ+vvvd75KZmdn2vwQRERERkVSKJp95idcfPwyqSlv//ZGhtZl5dSuf8QnwI8Pht6NaPx6J6rLJZygUYufOnVx00UWcddZZnHfeeRQUFHDnnXfyr3/9i+XLlwNu7mevXr2iiWGyrVFmzZrF6NGjGTZsGL///e9Zs2YNgUAget/ni/2a/X4/f/vb3xg1alTCz0svvVRnGK6IiIiISIcTqqfyCW2z3Um08plXNwGOzEeVtEj/sNs02bFjBzfddBOHHXYYTzzxBIMHDwbgpZdeYsWKFUybNo0TTzyR6667jocffjj6uQED3OpYoVCIigr3B/uwww7jzTffpF+/fgQCAW644QauuuqqpO8NBoNMmjSJp59+OuH6tddem5CwioiIiIh0SLWH3fqzIVTtjqvLWv/90cpnN6hd3InEVr4ZaXtdNvns2bMnL730UtJ7e+65J7fccgsA06dPjw6ZBaJJo9/v5/333wdIWM02KyuLGTNm1PveMWPGcPjhh9e5/uijjzb9S4iIiIiItDeRBYcyvOSz+wDYtsodt8WCP/GVz9oisW1cHLu2eSnk9oKCfq0fWxfXZYfdNlZ84pkKfr+f7Ow2WGJaRERERCQdalc+CwbG7sXvAVqfLV/FVqxtjmCl9/5uSWLzht1Wbo9de3Ksm/8prU7Jp4iIiIiIpE7tOZ/dB8Td20XyWRNwiwD95ZLmv3+LN680aeXTiy2SoEqbUvIpIiIiIiKpU7kNsgpg9Tx37o8b9VdT1fBnd6x37Vezm//+hd7aKhk5idd9GQ0nn5GkWVqNks9GCoXqXxmrurqaJ598slHPueuuuwgGg9TU1CQ8s7q6usUxioiIiIikXdk66LF77PywC2PHoV0ssLnyHdf6UzBNLbLYUG6ha+OTz5okyeeiZ1v+TmlQl11wKBQKRffijBcOhwmHw/j9/mgLcOutt3LMMcdw6qmnRj9vjMHn8zFt2jS++OILANauXcvYsWPZZx+3We2WLVv47LPPAHjllVfYuXMnmZmZPPfcc/z5z3/G7/djraWwsJBp06a1xVcXEREREWk9pUXQfXc4/dewbhEMittLM1nl09pYojjzatf6M1MXz9UfuYWOnjwyNuczUvksHAbbVrrjyq2pe6ck1WWTz0svvZQVK1ZgjGH16tVkZ2fTv39/ampqGD16NBdddBE33HADPp+PjRs3sscee/DZZ59x0003MWTIEAKBAJMnT+aYY47hscceIycnh6OPPpqHHnqIb3zjG9HVcq+77joAVq9ezQMPPMC7774LwMUXX8zFF1+ctu8vIiIiItIqytbBgEOgcIj7iVcTN9pv/cfw0nfdMN3rPoduvWP3mpJ8fvUmzP0lXPi35PM883q5n1AwNhQ4WOGqq6c8CH8+z12rPUxXUq7LJp/PPfdc9Pjee+9l0KBB/OAHP0jo8+abb7J582YuvfRSpk+fTklJCRdeeCGvv/46xvvXmYceeohzzjmHyZMnEwqF2L59O1988QUvvvgiQHQv0K+++orf/OY3XHHFFfz4xz/mqKOOapsvKiIiIiLSVmqqYWcxdB9Uz/24yueCP8CODe74uZPhqoWxe01ZEOjlC9xzFz0bW9zoiEvr9gtVu4R360oIVkFmDgwd735WvQsVWxr/ToCKrTBrsktgc3s27bNdVJdNPhvjsssu45NPPiEvL4+TTjopen3s2LEceOCBPPvss5x77rm8+eab9O/fnxNOOIFHH32U/v37M3bsWIDoXqATJ07k7bffZunSpRx44IGMGjWK/Px8QqEQpaWldO/enXHjxvHAAw+k5buKiIiIiLTY9jWujZ/zGS+wM3a8+fPYcWSF2ohdLUyUzOxbY8fhBhYPKi2CBU9BVr6rlP7gDfjVgbDxs6a9b8EUWDwNeu8F37ix6fF2QWlPPh9c8CDLti5L6TP367UfN42+qcXPycrK4oUXXmDu3Lnk5eWx995788wzz3D++eczdepUAIYNG8Yll1zCzJkz+eMf/8jWrVspLS3ljjvu4Dvf+Q6nn346AMXFxVx66aWce+659OjRg0WLFgFQVFTEtddey6uvvtrieEVERERE0mrtf127++HJ70f21wyHYHOtHCAyHzOyMFCoBvyNSVdM3UvV5fV3X/Z31wbi+pQVuZ+NS6D/wY14J7HvGp9QS4O02u0uzJs3j1deeYVnnnmGyZMnU1NTw4YNG6L3S0tLGTduHPPnz2f8+PF8/PHHHHrooZx//vnk5uYybdo0SkpKeO2117jiiivS+E1ERERERFpZZLhst76J1y+Z47ZfqfKSz22r3IqzvfeJ9YnMB83p4Z23YC/OQAPJ59YVDdxb2fh3fP2Wa5tTpe2i0l75TEWFsjUdffTRZGZmkpWVxdixY7n77rsZPXo0b73l/rD16NGD+fPnc/rpp/Paa69RVlbGzJkzueiiizjyyCP58MMPKSws5PLLL2fRokWqcIqIiIhI5xXZSqX2gkF7HAG7j4xVPiNDbvsfBCVfeZ+NSz4rSlwyml2w63eaZJXPHfX339TA8Fp/1q7fF7HHWFj7AZRvbvxnuri0J5/p8MADDzBjxgwyMtzX37BhA1lZWTz9tNuQNhAI8K1vfSvav2/fvjz44IP8/ve/54QTTiAcDtd55tatW5k0aRK/+93vqKqq4r333uOSSy7hwQcf5J577iEzMxNrbZ3PNbR/qIiIiIhIhxJNPpPs05nTMza3c/NS1+52IPzvr+54zl1eP6/y2dhFh5L8HbvB5LNsnWtN3W0XsXX/nl8vn5dKlRY1/jNdXJdMPm+++WZuvvnmXfa77LLLADjllFM45ZRTAFi5ciXnnXcel14aW0GroqKC4uJinnnmGdasWcObb77Jueeey+TJk7niiit4+eWXueCCC6iurqa6Ora89Pr16zn99NP54Q9/mOJvKCIiIiKSBjX1VD7BrQgbqXxu+h8UDk2sbH7o7UYRHXZbzS6FgsmH5zY07Bag155w2dzY+Q9nw7MnNm3+ZjjoWiWfjdYlk8/GmjJlSp1rw4YN45133iE3Nzd6LS8vj88//5zMzEyGDx/Op59+Ss+ePes8Y9y4cYwbNy56PnDgQJYsWdKK30BEREREpA2FAq6i6EtSVczpGZvzuXmpq3rucwLMqjUNrylzPqvKXDvuejdU96M/uvNTH2r4c7sdADndY+c9vK1hgk1JPr0VdXdscElwU/Ym7aK04FAzxCeeEZmZ7g+b3++PJp4iIiIiIl1KqLr+eZO5Pd3iPFWlULIcdtvfbVNy6VuJ/aLDbhuxkE8kme27b2yvzW/cBHtPbPhzuYWJ5xk5rm1MtTUi5FU+sVC2vvGf68KUfIqIiIiISP2qd8CMK2NDZuvzvxmuollf8hlJKtcuBBuCfge484L+if2yvYpkY1aRjSSfOT1iW7VkdUve9+hrY8dZ+Yn3MryYm5J8hmvcCr6gobeNpORTRERERETq99+n4JMX4f3HGu43/SJYPieWyNWW41Um133o2sg2K90HJvaLJK+NST4rtro2tzBusaN63n/CXbDPSe44K6/WO70FkkJNrHz2GuqOlXw2ipJPERERERFpgLeabLJVZZNpaNgtuCG3APm7ubb2VimRz089F7avbfhd21a5tucQ6LGHOx4wov7+kXdl1k4+MwHT9Mpn4VB3XLqLOAXQgkMiIiIiIpJKtRO7iBxvnmUk+czrnbxffOV042LouUf97yrfDBjI7wdjroA9v9Fw8hlZJKj2sFtjICO7ecNu8/qo8tlIqnymQCgUSrqHp7W23n0816xZ09phiYiIiIi0vdpDWiMilc/tayCzW/2rwxYOix37dlErW/tfwILP55LWhhJPiJsXmiRGf3Zs6O6uzLnTVTv9GW6lXCWfjaLKJ3D33XczcODAhL07Q6EQvXr1YuTIkUk/88knn1BcXExmZiaPP/44M2fOxOfzsXnzZioqKhg6dCjhcJgzzzyTa6+9ts7nb7vtNs4++2zOOuusVvteIiIiIiItFxkW28hht7WrihGRhYQqttStel7yZiyBO/Cb7v4LZ7rq4s4SeGhPOOcZOPjcxM+tnEuTRCqfyaqzGdmNm2cK8N6vXbtluUs+S75uWhxdlJJPIDs7m6ysxLHpfr+fESNG8NZbbulnn88Via21WGs57rjj8Pvd/kUXX3wxw4YNY9KkSbz66qssW7aM2267jZdffpnhw4dHn3nllVfyxRdfAFBWVsb999/Pb3/7W6y1jB07lvvuu68tvq6IiIiISOupb9htfKWzdp89RrufiG59XBsKxuZTvnVPYvLZ2Dmo8WzYtckS5IxsqGlk5bP7ICgrgsO+DxsWw7I34Mt/wfCTmh5TF9Jlk8/999+f3XffHXBDYLOysnjhhReoqqoiPz+fWbNm4fP5+Pvf/84TTzzBmjVr6NGjBz179uTCCy8EYgmp3+9n8uTJ7L///tHnV1dXc+edd/Lmm29Gr61YsYJp06aRmZnJL37xCx588EEAli9fzm233dZWX11ERETIF0+OAAAgAElEQVREJLXiE8HIliq1xSefkX016xMZbhuuiVUjg5WJfRo7RDZZDCbJ7MOMbAjuhNXzYciRDT/H+GDEd+HQ78VW3P3zeXBnKbxyIRx4NhyoEY61NSr5NMb0A1611o43xmQCrwG9gGestc+2JICNv/gF1UuXteQRdWTvvx/9b7mlwT6ZmZnMmTMHgIcffpj+/ftzwQUXsGrVKq666qpov9NOO41TTjmFRx99lFGjRjFu3Dh8Ph9PPfVUtE9+fj733HMPN910E+effz4A9957LxdccAGDBg2K9nv55ZcpKCjgV7/6FXvsEZs4PWTIEB555JGUfHcRERERkTYXqSgC7H188j7xq+BmNjb5DLl9RqFupTOws2kxAvTZF1a8HRt+mxBfNnz+N/dz0esw7Jj6nxMKxL5Pj9jf97E29owDS5seXye3y+TTGFMI/BGI7NZ6NfChtfZOY8w/jDHTrbU7WjPI1hCpWu7KkiVL+OlPf0pRURGvvPIKBQUFPPDAA9H74bD7P9rZZ5/NyJEj+eijjwA444wzOPTQQwmHw1hrWbJkCTfeeCMZGRnMmzeP8ePHM2vWLL7++mtyc3Pp3bs3d9xxB+PGjUv9lxURERERaa7I9iQNDXONTz73PSV5n/jFgzJyG35nfOVzx8bISxL7RJLPM3/b8LPiTbwTeu8Fw0+uey9+ld3NS13yGQrC6nmw54TEvgnJZ9xqvNUdLi1qU42pfIaAbwN/884nADd7x+8Ao4D/NDeAXVUoW0tNTQ0TJ04EYsNun3/+eaqqqujevXu034gRI5gzZw4PP/wwBx10EDNmzODwww+P3p8zZw4PPPBANJmNLDj09ttvA27hoksvvZTzzz+f2bNnM2XKFEaNGsXdd99NOBxm/PjxvPrqqwwYMKDtvryIiIiISCqF43Z4yC1M3id+P8+c7sn7RESSz0A5fPCkO87vl9gnknxmdaPRsvJgzOXJ78UPBd6xwbVv3w/vPgLjfwrH/zx2PxSMJZ8F/WPXK7d5z9pFct1F7TL5tNaWAZjYH5ZuwDrveCvQr/ZnjDGXAZcBDB48OBVxptyzzz7L6NFuUnP8sNuqqiq+/PLLaL977rmH999/n507dzJr1iyysrK48847o/dPPPFETjzxxOh5/IJDyQwdOpQlS5Zw2mmn4fP5GD9+vBJPEREREenYIpXPiXc1rn/33Ru+H0k+P5kK21a5vTSDFYl9mpN8NiR+WPCWrxLbdx+plXxWx+aP9vC+S/dBULXdHWcXpCamj6fCB7+DS2bXv4VNB9KcBYfKgVygFMj3zhNYa6cAUwBGjRrVjGWoWl8k8QSiQ2MBcnJyOOSQQwBXtbz99tuTfn7ChAmEw+E6w3cjq+HWZ+zYsWzfvp2lS5dy7LHHsnDhQs4880xuv/12jjjiiJZ+LRERERGRVtLQsFuv8plsIZ9kGpt8lq137X6nwrJ/uON/3w09B0OvPd15qpLP+MrnsjcgHK6b8IIbBhwKQPmm2LW9J7qFhyq95HNXld3GKt8Im5Y0/vfazjUn+fwQGAe8CowAPkhpRGlQXl5OIJC4WlY4HGbx4sVMmDAh6Wc++eQTampq6mzRUl1dTXV1dZ3+4XCYk08+mVAoxBlnnMH06dMpLHRDEhYuXMg999zD1KlTKShI0b+SiIiIiIikwgpvL83qOjWnmKKFrvX5G/fM7rsY+Rd5zs5il4jmFrr5lDXVrgoJ8N1prk1Z8pn493pWvg19hsPyOYlV0cWvuPbTl+Cbv/fizYRwMK7ymaLkM+QtjBS/UnAH1pzk84/AP4wx44EDgP+mNqS2d/fdd9e55vP5KC4urpNc7soFF1yQ9LrP52P27NlJ7x1xxBHMnDmzSe8REREREWl11sJKL/ncvjp5n6pS+NM33XFjK3Td+jZ8P2FxohyXzIWqoXxz7Hpk2G1mipLP/P6J54EKl+yCW1QoFHRJYOFQd+3E+2J9/ZkuUYzM+UxV5TMUcL/Txib17Vyj67fW2gleuxo4AZgHTLTWhhr6XAPPa87H2lRTE8/W0BF+TyIiIiLSSZWtix1vXZG8z4ND405M8j615fVp+H7t5HPQKHe8/M3Y9VTP+ey7b+J5TRVUl7njrV/DPV7MkfRnr+Niff1e5bMyxXM+w8HEqmsH16zBw9ba9dbaV6y1zdq8Jicnh5KSEiVWu2CtpaSkhJycXeyDJCIiIiLSGoq/iB1vWwXBqrp94rdZCexiq5Ee3mKk/Q9quF/8MNOKLTD4SFfhjAx5hVZIPvfznucljivnwpLpdftFqqEZ2bFrvkxXpYwMu81I0d/fQ0H37E6iOcNuW2zQoEEUFRVRXFycjtd3KDk5OQwaNGjXHUVEREREUi2y2iu4JHPr19DvwMQ+eb2hosQdNzQvFOC6JY17r88P3/ojTL/InWdkuyRzzfxYn2CKk8/d9ndtpLL50Qt1+1ibPPn0Z7pkOFL5jE/IWyIUBH9aUrZWkZZvkpmZybBhw9LxahERERERaaxtq1w75GhYPQ+2fFk3+ewxKJZ8hmtS9+4Dz4LXe7g5peAWH4oX2OmGpKZqMZ5ufdx2KoOPgudOTt4nXBOXfMZVNyu3ud/Bh8+585Qln4FONey286TRIiIiIiKSWjVVbnGgbz4Fjx6UvLJZE7fTQyhQ935LXPd5LKHN6xVLcsEln6mqekaM/ynUNPAdgpVu4SNITAojFc+IcLOWxakrXNOpht12jg1jREREREQk9cLenMNIopUsuUxIPoOpfX92PuT29I5rLeKz4VMwrbAKrD+z/lV7a6qTD7utvQdqqiqfVaWdZo9PUOVTRERERETqEw65lWcjQ1trJ5+V2xOvpTr5jFe7Ari2lXZ8NMYNqQ1W1L1XUxlLPhsaDpuK5LMmAMveaPlz2pHOk0aLiIiIiEhqRRa8SVb5XDEXHhzitmOJrBAbbsXkM5IA9xneeu+IiJ/Pud/pseOaajfs1p/tktT6pGLY7Y71LX9GO6PkU0REREREkmto2O3mz2PHfYfXvZ9qkb0/++1im5ZUyMx17T4nwXkvwJm/dedBr/KZMOQWtwpuwnkKKp+RBPbMx1v+rHZCyaeIiIiIiCQXqnEVx+iw27jKZl6f2PGYH7t2xPdaL5ZIDMmGw6ZapPLpz3TbvhT0d+eROZ+1k8/abAoqn5GFljLzWv6sdkJzPkVEREREJLlwjUu+jHEV0ITKZly1b+jRcGdp68YSmfN5wFmQvxvsOQG6D2qdd0WSz0i1NXL+v79625/sKvlMYeXT13lSts7zTUREREREJLUiw27BVfviK5/xq9zm92/9WCKVz+4DW38oamZc5RNiyecHT8BB5ySpfNYadpuKOZ+RymcnSj417FZERERERJILBWMJmL9W5bOmKnbsa4O0IqdH678jIsOb8xlJvOMXF1r3YSOG3aai8qnkU0REREREuoKNS2DVu7Hkx5+VWO2MP24LZ/wGjvkZDB3X+u+KVD4zkiy0tG0V9ByS2H/wkYltSofdtsJepmmi5FNERERERGIqtkLZBnj+NHdeuta1/qzEYbebl7r2/1ppv83auvWB425rm2QsUnXsOdi1g0bD6Mti94++JrH/cbfBVYvgh7PcXNRUDLu1Sj5FRERERKQz+/VB8Kv9oMpbQGjHJtf6M2HlXHjf23Zk2yrodzDstl9awmxVpUWujewp6s+AUx+K3e+9d2J/nx/67OOOc3pA5baWx6BhtyIiIiIi0qkFdyaeH36Ra/1ZULYOZt/qzqu2xyqDnc12r9rbe5/k97O61f/Z7rvDjg0tj6H4C9cq+RQRERERkS4hOuczM3YtHILK7ZDbMz0xtZVew5JfjyxIlExuIQTKWzb0NhyCv1/vjk3nGXbbedJoERERERFJvUgCFr+3ZXWZq3zmdNLk85LZDa9q29Dqvn5vkaKaasjKa977E1YS7jwpW+f5JiIiIiIiklp7T4TDf+iOI0kVwOr5rrrXltuftKWBh7qf5ogkrDVVLUg+41YS7kQLDin5FBERERGR5A75dqzKFz/sdtp3XdvZh93WdvqjkF3QcB9/ku1Zmioh+ew8KVvn+SYiIiIiIpJamXGVu/jKZ0RnHXZbn1EX77pPhrdHaEv2QY0fdhusaP5z2hktOCQiIiIiIsnFDxvN6V73flerfDZGdNhtS5LPuM/22KNl8bQjSj5FRERERCTGxKUImXFbihQmWfm1q1U+GyM67LYFyWfks9/5M3Qf0PKY2gklnyIiIiIiEpOVH3ccV/nsu1/dvqp81pWKYbfBStf661ltt4NS8ikiIiIiIjHx8zxzC2PH/Q6s2zc7yVDcri7LqxZX72j+M0qWu7ZwaIvDaU+UfIqIiIiISEx8tTO/f+y4zz5J+nare62ri8yNrS5r/jN2bHBtz84z3xOUfIqIiIiISLz4oZ7+uM0x4rdaiVDyWVekGly1i+Rzx8b67wUq3BYrGRp2KyIiIiIinZUN13/v5jVwy/rYuc/f+vF0NJF9QBsadrvmA3hkX1jyavL7gZ2dMrFX8ikiIiIiIjE25Kp3F71R915OD5cU7XV828fVUUQWHGpotdt1Hya2tW1fk3xf1Q4uY9ddRERERESkywiHYPhJMGx8/X2+9zKEgm0XU0cS3Wqlgd9PsMK1kUQ1XqACvvxn6uNqB1T5FBERERGRGBsCs4vhtP7MxIWJJMbnBwyEAvX3qSp1beVWmPcYWBu7t+QV1x55VauFmC6qfIqIiIiISEw45Ba7keYxxi0U9MUs2PIlnPdC3T4bFrv2w+ddu//p0GtPdzz/SdeeeG+rh9rW9KdKRERERERiwiHwaYBki/izYNMS91NTXXfV2tpDcmu8+aE7NsGWL9yxMa0fZxvTnyoREREREYlpzLBbaVj8tjTJtlyxocTzgDcHdPmc1oupHVDyKSIiIiIiMeGQtlBpqfiVaiPzO+OFaxLPyze5dvmbrRdTO6DkU0REREREYqzmfLZYfOWzOknyGaxKPJ/2XdixEb5+q3XjSjMlnyIiIiIiEhPWsNsW21XlM7iz7rWihbG+oy9rnbjSTP+kISIiIiIiMVpwqOUSks8kcz6DlXWvRRLPs34Ph363deJKM/2pEhERERGRGC041HK7qnxGFhgCyO/n9fOS1Pghu52Mkk8REREREYnRgkMt11DyaS0EKyAjx51n5bu22ks+O/F8WyWfIiIiIiLiWKsFh1IhPvmsrjXsNhRwv+P+h8TOQZVPERERERHpQmzYtRp22zIJ+3zWqnwGvMWG+h3o2gEjXLuz2LWdOPFX8ikiIiIiIrB8Djwxxh1rwaGWaWjBochiQwMPhe/PgLOnQHZ3KF7mrnfi5LPzfjMREREREWm8v/8Utq1yx6p8tkx85XPn5sR7QW+xocxusNex7rhgAJStq/vZTkb/pCEiIiIiIpCZFzvWgkMtE1/5/PotuLMHvHE9rHovlnxmxf2+83pBRYk79in5FBERERGRziwzN3bciYd+ton45DNi0TPw/GmxbVbif9/ZBXGfVfIpIiIiIiKdWY9BsWMNu22ZjCTJZ8Tmz12b2S127eifxI47ceKv5FNERERERKB7XPKJTVsYnUKk8rnnhLr35j/h2vhht0PHxX1WlU8REREREenMIvtNAlRuT18cnUEk+cztVfde5PccP8c2XnwFupPpvDVdERERERFpvPjks/YKrdI0keqlP8sNow3XuHNfJpSudce1k8/v/xWW/xtyerRdnG1MyaeIiIiIiEAoCHl9YK/jYMyP0x1NxxapfPozoOdg2LrCnffeG4qXuuOsWsnnXse5n06sycNujTGFxph/GGMWGWOeao2gRERERESkDYVD8OmfoaYKzvkD9B2e7og6tuhqt8YlnwD9D4Z9Jsb61DfsthNrzpzP7wNTrbWjgAJjzKgUxyQiIiIiIm3py1muDZSnN47OIrpokIUDznKHp/0a9j0tSZ+uoznDbkuAg4wxPYE9gLWpDUlERERERNrUsn+kO4LOxZ/tWgsc/gMYdgz03gsqtqYzqrRrTuXzPWAIcA2wFKjzGzTGXOYNy11UXFzcwhBFRERERKRVbf6fay9/J71xdBbxVU1jXOIJkFsIffeHSU+kJ640a07yeQdwhbX2bmAZcHHtDtbaKdbaUdbaUX379m1pjCIiIiIi0poCFXDAJBgwIt2RdA7ROZ+19ks1Bq78AEZe0OYhtQfNST4LgYONMX5gDNqBVkRERESkYwtWQGa3dEfRefj8rrVKleI1J/m8H5gClAK9gJdSGpGIiIiIiLSt0rV1t/6QFjBeq+QzXpOTT2vtAmvtgdbafGvtCdZaLYklIiIiItJRbVzi2mV/T28cnYnxkk9VPhM0p/IpIiIiIiKdxdYVrj30e+mNo1NR5TMZJZ8iIiIiIl1ZRYlrR12S3jg6E1U+k1LyKSIiIiLSlVWVuja3Z3rj6FRU+UxGyaeIiIiISFcWqHBtRm564+hMVPlMSsmniIiIiEhXFqyAzDzwKTWQ1qU/YSIiIiIiXVlgp0s+JXV67ena3Q9LbxztTEa6AxARERERkTQKVmiPz1QbNAr+77/Qd990R9KuqPIpIiIiItJVVZfD8n9D3/3SHUnns9t+sbmfAij5FBERERHpuhY8BRVb4Jgb0x2JdAFKPkVEREREuqLK7TDvNzD8ZNjjiHRHI12A5nyKiIiIiHQ14RA8OMQdH3tremORLkOVTxERERGRrqZsvWszcmHAIemNRboMJZ8iIiIiIl1N9Q7XnvVEeuOQLkXJp4iIiIhIVxMod2129/TGIV2Kkk8RERERka7ms7+4NlP7e0rbUfIpIiIiItLVLHzGtT0GpTcO6VK02q2IiIiISFdiLeQWwuAxUDgk3dFIF6LKp4iIiIhIV7J9NezcDHtOSHck0sUo+RQRERER6SzCIfjLj2Ddh8nv1wTgnze740Gj2y4uEZR8ioiIiIh0HqVrYckr8Ifjkt//4En48p/uuN+BbReXCEo+RUREREQ6j/Li2HHRh1BdDn/+Nqx8x10rW+/afU8Dn7/t45MuTQsOiYiIiIh0Fl+/FTt+Oq76+eUsmFwEn8+AvD5w9pS2j026PFU+RUREREQ6gx2b4O1f1H9/5tVQvgmy892PSBtT8ikiIiIi0hmUrm34/pr/unbCLa0fi0gSSj5FRERERDoyayEchqrtsWs/+Idrr/4IbvaS0h3r3f6eI77d9jGKoDmfIiIiIiId2wuTYOVcOPi82LWhR8OdpbHzrHwIlLv5niJposqniIiIiEhHtnKua5e84trL5tbtk9/PtXm92yYmkSSUfIqIiIiItHebl8LOkrrXNy5JPB86HgYeWrdfwQDXKvmUNFLyKSIiIiLS3j05Fn4zou71349LPO81rJ4HWNfstn9KwxJpCiWfIiIiIiLtWeU21wZ2JF7f9HndvpHhtbX5s1w78oLUxSXSRFpwSERERESkPdu2Ovn1ooWx48N/ABVbYez/Je876QnY9FkDlVGR1qfkU0RERESkPbIWjIFtq+peg9jWKqMvh4l3QFa3+p/VY3f3I5JGSj5FRERERNqjv17uqpsDR8aubV8DhUPcceV2MH445cFYQirSjin5FBERERFpbyq2wuKX3fHWFbHrX82GQ78H1TugqhRyeijxlA5DCw6JiIiIiLQ3RYsSz4/5mUs0i5fBH8+AR/Z1yWduz/TEJ9IMSj5FRERERNqbogWJ58YHvfZ0VdB1H7prFVtcQirSQSj5FBERERFpb77+T+L5qB9C4bDEIbgr5kKOKp/ScSj5FBERERFpT6x126LsMcadj/8pFPR3lc/tayEjJ9IR8nqnLUyRptKCQyIiIiIi7UnlNqipggMmwXG3wx6j3fXCoWBDUBOK9e25R1pCFGkOJZ8iIiIiIu1J5TbX5vWBYeNj1/N61e2rOZ/SgWjYrYiIiIhIupUWwQe/c0Nuq3e4a9n5iX382bHjb05xldGRF7ZdjCItpMqniIiIiEi6/fUKWPUuBCtjw2yzaiWf2NjhXsfCiG+3WXgiqaDkU0REREQk3WzYtf++C/Y73R3XrnwOOQp67QUHnQ35u7VtfCIpoORTRERERCTdBo6E1fPc8bI3XJtdaz5nVje45qO2jUskhTTnU0REREQk3YKVda91H9j2cYi0IiWfIiIiIiLpVr4JegyOnQ8+ErLy0hePSCvQsFsRERERkXTa8KkbajvsGDj7Kagogf3PSHdUIimn5FNEREREJJ02L3XtCffAwEPTG4tIK9KwWxERERGRdAqUu7ZgQHrjEGllSj5FRERERNIpsNO1tbdW6QRsIEDFwoXYUCjdoUg70Ozk0xjzpDFGg9FFRERERFriw+ddm5Gb1jAaYq2l5LnnCZWWNulzW56awurvX0j5u++2UmTSkTQr+TTGjAf6W2tfT3E8IiIiIiJdRzgEW1e4Y1/7HZRYtXgxmx98kPW33troz4Srqyl7w+1ZGm5i0iqdU5P/hBtjMoE/AKuMMZNSH5KIiIiISBcRme/Z3vndOqXBtUWN/siXR4wmsHo1AOHKqlYJSzqW5vzzyoXA58AvgdHGmKtTG5KIiIiISBdR7SWfR16V3jh2pSYIQHjnzkZ1tzU12EAgeh6urGyVsKRjaU7yORKYYq3dCLwIHFu7gzHmMmPMImPMouLi4pbGKCIiIiLSOZSug4f2iW2vEllsaODI9MXUCOGqplUuQ9u2AZA/8Xj3+cqKlMckHU9zks/lwJ7e8Shgde0O1top1tpR1tpRffv2bUl8IiIiIiKdxwtnws7NMOdO2FkCFVvc9ezuaQ1rV6LJpzGN6l9TUgJAjzPOBCC4Zi3W2laJTTqO5iSfzwDHGmPeAf4PeDi1IYmIiIiIdELbVkPJcnf85Sx4aE9YMRcwsPvhaQ1tV2xVtTtobPK5xSWfGX16A1A6YwYrTj2NDbffriS0C8to6gestTuAb7VCLCIiIiIinddvDql7bcEUN+S2W++2j6cJKhYuBMCXl9eo/qESV9HN6B37XoGVKwmsXEnh979PzvDhqQ9S2r32u56ziIiIiEhnV7kV9p6Y7igaZINBtk2bBoC/R48694ObN1P25psJ1yKVT3+fPnX6a9uVrkvJp4iIiIhIWxo4Ek6Nm7nWzpPPcFUVhEIAVPz3v1jvOGLtjy5j3dXXEK6ILSpUU1KCyc7G160bQ176c+LztPJtl6XkU0RERESkLWXlw+gfxc4HHZG+WBrBVlcnnFd99lnCefXXXwOw7rrro9dCW7fiLyzEGEPmwN0T+scnqcmUzZrFjv/8pyUhSzul5FNEREREpLXt2Bg7zsh2rfFBRg742vdfySPJZ6+LLgKgfN68hPv+7m6l3vK5cwlu3gxAeGc5/oICILboUES4ov7Kp7WWdddeR9GP/y81wUu70uQFh0REREREpIm2rowd+73k88aVyfu2M+HqAAA5Bx9M9r77UvnxJwCUzZ5NeGcFNhjEl59PuLwc61U1Q+Xl+PLzATB+f+LzGtjzM34+aDgQwJeVldLvIuml5FNEREREpDVZC6vfi51HtlvJ7ZmeeJrIBlzl02RnkTV4D6pXuqR53TU/cdczM8kYMIBweTk127Z5xzvxF8a+36DfPYmtrGTd9T/FNjDnM7I/KEDN5mKyBu1eb1/peNp3jV9EREREpKP7dBq8dW/sfK/j0hdLM0SG3fqys8katieBVasJ7dgRux8MRofYrv7u91h13rcJlZXizy+I9ik49lgKTj4ZaHjYbXzyGS7fUW8/6ZiUfIqIiIiIpErFVph9m2sjyopix9cvhZN+0fZxtUDYSz5NVjY5++0LNTVUfvJJQh9fQSzRrP7iC4Kr1+DrXpDQx/h8mNzcBle7DcUnn1oVt9NR8ikiIiIikiqLnoX3H4dPvO1FZt8eq3p+bzp0H9juFxiqzXpzPk12FiY3F4DKxYsT+vgLCup+Lhisc82Xm9vgnM+akljSXnuVXen4NOdTRERERCRVbNi1Zeugphrefyx2r4MNt42w1VWAG3Zr87oBsOXx3yb08SVJPntdeGGda77c3IQ5n9ba6PHWZ55h88OPRM9V+ex8OtY/u4iIiIiItGdV3mqtpWvh9WsT7/k7Zt2nZts2AEx2Nr683KR9/AX5da/1LKxzzZeXG53zWVNczFdHj2PNxT+kYuHChMQTwFZVtTT0VmVDIXbMmYMNh9MdSoeh5FNEREREJFUi+3kufR0+/TOMuz698bSQDYfZePvPgUjymZfYIcMl1N3GjavzWX9+tzrXTG4eYW87lvJ33iW0dSsVH3xA1ZLP6vRtaGGi9qB05usUXXU12/70p4Tr8dVcSaTkU0REREQkVTYmzoXkuNvh21PhvBfSE08LbX0hFrfJysKXm1j5HPbqdPaa82ZC8pl/7LGuf27dKqkvbsGhwOrV0es1W2MLDUU+H9y4IQXfoHXYcJgNkycDUP7evIR7y/Y/gI333JvsY11ex6z9i4iIiIi0N9U7YMtXMPAwWP+Ru+bzwf6npzeuFgisXBU99mVnQ1ZWwv2c/faLHu8z/30IhfD37Elo+3ZMkoWVfLm5BMvK2LlgAVufey56feszz8b65OWRMWBAQnLa3hRdfU30uHrZsuhxqLwcgG1Tp9LjrEnsmD2bvtdfjzGmzWNsj1T5FBERERFJhY1LAAuH/8CdDz8lndGkhA0Eose+3FxM7WG3cTIKC8no0weTkUFGnz5J+/jycgmsXEnRVVeTOXgw/W65pU6f0PbtZA0Z0q6Tz/J//zt6XFNcHJ0XG1y3HnBV4o333kvJH55m24tT0xJje6TkU0REREQkFb5+y7V7ToAfzoZzn22od4dgAwEyhwxm/2VLMVlZmMzMFj3PZGVjq6oIl5Ux8P5f4C9MXJTI37cPvS+7jKwhQwiuiiWfgbVr29VcysyBA+l+6ins8fTTAFQsXAhAcN06wEvaQ24hok333adFiTxKPlduvvcAACAASURBVEVEREREUmGVN/evxyAYPAay6q8SdhQ2EMAXN9Q2fvjonn9/o8nPM5mxWX8ZffpEt3EB2O1nNzD83XfpNmY02XvtRai0lKqlSwkUrePrE05ky+OPN/NbpF64uhpfQXe6jT4Ck5tLxX8XABBcvz7ap/qrr6LHO/71rzaPsT1S8ikiIiIi0lLzn4Q170N2D/D50x1NythAAGpVOwc+9BDDZvyV7L32avLz4iunvm7dyNhtt+h51p57Ro9zRxwCQHDjRsLlOwAonfG3Jr+vtdiqKnw52ZisLPJGjqRigZd8epVPABsMRo9DZTvYdP/9FD/xRJvH2p5owSERERERkZbYtgr+5VY+ZciRaQ0l1WwwgC8zcZGhHme0YAGljFj64cvLI/+YY+h77U/I3mcf8idMiN6LrJRrq6uj+33WFBc3/70pZAMBwjt3Rv+RIW/MGIp//WuC69cT8uZ+AhAO4+/Rg1BpKaV//SuVn3wCQN8rr3TPCASTbkfTmanyKSIiIiLSEp+85Nrv/BnOfa7hvh1MOBDA1FrhtiVMhqt8xs8f7XPFFRQcf3zCkF5fTo57f1UVYS/5jFQSKz/5hFD5zpTF1FSlb/wdgO1/+QsAeaOPAGD5ccdH58jirfTr790bIJp4ZgwYAMDGe+7ly1GjCFdXt2ns6abkU0RERESkOdZ9BOXFUF3mzvc7rVPM84xnA8HUJp9ewulrYNVcAJPtks8NN08mXFEZvR6urGTVd77Lumuuqe+jrSIcCBAqc/87mwxX8ezn7fOZe9BB0X7BDRswmZnR1X593brh79Ejej+yevD26dMBCKxc2frBtyNKPkVEREREmuq5U+EPx8IrF0LlduixR7ojahW2smKXiWJTGG/Y7a6e6cvJjh6Hykqjx4FVqwDY6a0uuyvl77zD+ltubfFKuWsvv5wvR49x8exwc1DzjxkPuIS68IILAKj8+GMCy7/G36uX+x7durHnG6/HvktJCZVLPoueB4uKWhRXR6PkU0RERESkqVZ7K9uu/QB2bIDs7umNpxWEKyup/mo5xA2HbanIare7qqYab9gtwM533okeV3662B3ELebTkLWXXU7pa68R2r69iZEmqpj/AQDWWoJr1gD/z959h0dVbQ0c/p0p6Z0UQhIg9A6CdARpUq6oKBZEUD+s2AugIorl2q9SFHtXFOxSBakCggLShNACISGBFNLb1O+PPZnJkBBaGsl6n8dnztmnzJ4QcNbZe6+F24jmqTVJ9cFBgCrJYggLI+yhBwm6fgwAR66/3nmepfQa0XpAgk8hhBBCCCHKczIeCssJDopcI3HYbRC/GloOrb5+VZPsn38GIHf58kq7Z8m0W83Ts+LzSgWnOUuW4nuZGmUsWTt5NswpKc5t0+Ej59BLd3aLxdWXX3/l5OdfqD6WSp7EKXU89X5+gAo+AULvvZewcqYKp77yKgcuH1hv1n5K8CmEEEIIIcSp8tJg9iXwvzZgs7ofyzikXoe97GobMLX6+lYNTAkJpL7+RqXf15KeAYBnq1YVnqdpGi03bnDuN5g4EYxGZ0BcEtSdTvq773Jw4CDnfsl03XOVvXgxcR06OveTpz5R7nn2U35HbEXFZfqpd6wDLaF5eGDLz8dy/DiWEyfOq38XGwk+hRBCCCGEAMg9DjMCYc8vkONYi2cpgrjF7uclOdYbNh8EY+fDlMN1KtGQKTGRQ8OGYysoAKDJN/Mq7d6+/fqi8/cn/NFHzniuISSEiKefJnDMdSqjbKmptrpSU15zV67kxCuvuq3rTJs12+1e5xt8pr/7brnt+qAg9wZrqZFPgwF7oUqSZIhw1THVNI2gsTcRPmUKbeP2EvH0NNflObnn1b+LjdT5FEIIIYQQAmDfEvW6YAJcOtHV/s9X0O4qtR23BJZOUdvBTSG8TbV2sTqkvfWWc9uzZQu8O3as4Oxz49e3L63//uuszw+5ZVy57SXBHUDSffcDULx/H+GPP45Xu3Zu53rExp5XVlm73Y7VMVJ7qhYrf3dvcKyLbfTaq/j27Uv6O+9QsGULxoYN3U6LfPZZ53bAsGEcf0btW1JTgfbn3MeLjYx8CiGEEEIIAeAd7Nre8rF6je4Oyf/AqhdhRhB8O1a1x/QEo1fZe9QB1tw8vDp0oG3cXpotXOi+trEW8O3bF5sj+Ex/7z1ne/7GP0l7+x23NZpRc2bjERtL8aFDp71f0sOPcGjkf8q0Fx84gDUri8j//peot950O6bz9XXbj/zviwTddCMBI0diaNCA8KlTafzF53g2b37a99UHBtL6n23oAgLIKZURty6T4FMIIYQQQggAfTlJcGL7Q34qrHsdcEzr9PCDW36o1q5VJ3thITpv75ruRhkRTz2FZ8sWeMTGOoPPtJmz3M7RDAbnKGfkSy8RMHQoPt26YoqPx3witdz75i5bhik+nuRp09wS/1iOHwfAo1ksPj16VNg3j+hoImfMcJWS8fTE9wzXAOi8vQm86ipyVvxeL5IOSfAphBBCCCEEgNXx5f/m71xt3W6HLuNg4u/Q7TbV9tAO8PSv9u5VF1txMZp37RvVDZkwnmYLF6Lz9sZWWOhc4+nbr5/znNzly4kfpaZIe8Q2BVzJjQq2lK0NajOZnNvZP/yoSss4WLNzADVCaWjQgLZxeyv185Tw6a7WsxbvP1Al969NJPgUQgghhBACwOIIPkNbwMCnVUKhoBi4Zi7EdIcrZ8L0DPANrfg+Fzl7USE6z9oXfJbQvL3AbMaWlweAb6+e5Z7nGRurXlu3BiD/zz/LnHPihRfc9i3paeT8thy7zYY1R5XU0Qe4arg2evUVot+de+EfohSPJo0BMB9LKnPMfOIEhbv/dZtKfDGT4FMIIYQQQtQvOSnwaixs/cy93VKkXg1eMGAyjP/J/bimgb52rX+sCrbColo58llC560yC6dMf0bt+/oSNXMmHi3c11eWZKQ1hofj27cvRbv/LXOvoj178WjRHL/BgwHI+uZbjj30EJlffYUtV2WgLR18Bl59Nf4DB1bq5ykpx2JOTilzLGfRIo6MGYO9jkzJleBTCCGEEELULyfjofAkrC5Vp7M4Fza+rbYNtTfwqg62/Hx0PrW3dEzJetTcZcvUvn8AAcOH4T906Gmv8erYgeIDB5xrRUvYCgrwbNGSiCdUnVarYzQ1e+EirNk5aN7eaB4eVfExnHT+/mje3uXW+rRmZqJ5eKDV4j+PcyHBpxBCCCGEqF9MKsAg7zj89aHa3v8bZByAsLbgFXj6a+s4u82GNTu7bB3LWsQYHe0WEPr1vwyAsHvvJWqOqu/p2bKl2zXeHTuC1UrR3ji3dlthITofH3R+fgAUbt0KQNGuXVjS09H7V/3aXk3TMIaHY04tG3zmrV2LLjAAzVHK5WJX9+cNCCGEEEIIUVpxrmt7yePQ7moocNRzvG0x6PQ1069aoGj3brDZ0HnV3tFfv359abXlbwq3/YPOx9s5LVbz8MB/yBDCHn2UgJEj3K4pqf1ZvC8O70u6ULBpEz49eqjg09sbvSP4LK1w61b0gQFl2quCISICU/xhrHl5zr5YMjMpPnAQrw4dqqUP1UFGPoUQQgghRP1SlO2+/0ZL2K+mcOJde0f8qpo1L49jjz0OgHfnzjXcm4rpPDzw7dUT706d3No1TSP0rjvxiI52a9c3aADA8eeeJ2/NGo7e/n/s790HW3Y2Oh9vNKMR7ZSA25ycjC6gekbBvTp2oHjfPpKfeAIAu91Ows3jAAi5/bZq6UN1kOBTCCGEEEJUH5sVNr8P5sIzn1sVshLh2Nay7YdWqdd6POqZ8tQ0zImJeHXogG/v3jXdnUqlKzVNN3flSgBsOY5SKiEqMNWVM/pZOtlQVQp//HH8BgzAnJAAgCU52Vmv1BAcXC19qA4SfAohhBBCiOqz5xdYOgXWvHzmcytb4l8wswNs/xoadoQZ2XDzgurvRy1VtHs3AP7DrqjhnlQt89FEt32dI7OvZ9OmAPj06OE8Vl3Bp6ZpGKOiMKccx263U3zQVW9U8/Kulj5UBwk+hRBCCCFE9TEXqNe8NPVamAl2u+u43a5GRytD3GLYu8i1f3yna1tzfA1uWSrQemhH5bzvRaqkVEmDiRNruCdVq3CH+59zwJVXAhD20IMEjx9P+OTHncc8HLVCq4Nnm9bY8vIo2rGD7F8XAmBs0hjPVi3PcOXFQxIOCSGEEEKI6lFwEo7+qbZ3zIMhz8L/WsPgZ+Cyx9RU3A8GQkBk2RqbZ8tigk3vgN0GK59XbY/tB99Q90A0xRGIahp0GQdhbSC46Xl/tLrAnJyM35DBaLq6PT5VumZm27i9zm2f7t3x6d4du8XiauvWtdr65dmsGQDHHn0Mc3IyAM2XLaszmW5BRj6FEEIIIUR1WfMy/POVa/+bseq1JEj8b0NI2+taf3k+Ns6G32e47gmqhMrBlRC/GmJ6ORpLjbZeMxf6Pnj+71kH2O12zMkpGBs1qumuVJnQSfc6t/2GDKblhvXlnqcZDM66ml4dO1ZL3wCMMTEAzsATqFOBJ8jIpxBCCCGEqC6Jf7nvJ29zbZcuf+J5ARlGD68FvQdYTa62z/4DrRylN276WgWi9XyU81THn52BvaAAY2TdDT7DHnyQ9LnvAuAR0xiDIwNueZr9+iumw/HVWnLGGBGB72WXkf/HH4Aaia1rZORTCCGEEEJUD4+y2USd4te4totzwGZT6z93LoBj2yAz4cz3t9kgYSN0uw2eOQnTM1zH9i8Fo4+aftv5Rmjc83w/xUWlKC6Own//rfAcu8lE1gKVeCngiqHV0a0aZy8uqvC4R3QUfpddVk29cQl78AEA/IcOocmXX1T7+1c1CT6FEEIIIUT1KKmhOXBa2WO7vlevMb0Au6q7eXgt/HgnfDgQ5vYqew2A1QyzusD2byB9P9gsEByrSqboDXBHqSm8JcmO6pHD14zmyHVjOHzjjRTHx5d7jjU/H4CIadMwRkVVZ/dqjP+QITXdhXJ5d+xI9Ny5REyfXtNdqRIy7VYIIYQQQlQPvRECY6D/ZPAKgqWTYegLsOld2POzOqfP/TB/E3w71v1ac4FKJmTwcG/POwGZh+Hne1xt/hGu7ehuahR0z8/qPeupoh07SZs1m+hZM8scszmCT52vb3V3q9pFvz0HAN8+fWq4J6fnP2hgTXehysjIpxBCCCGEqB6WYjX6qWnQ8y5VZ7Pvg3DdR+ATClfNgbajYNhLQKlEK75h6rUkQC0tL7VsW8tT6lTq9NDhOmgxuNI+ysUge9Fit31bbi52m63Meba8PAB0fnU/+PQfMqTWjnrWBxJ8CiGEEEKI6mEuBEM5CVya9oUph6DrBLXf+z5VfgVgwBOqVIpnICx6BI5uhqIcdawwC5ZOdb/XHSvB07/qPsNFwm42k/y4qlepD1QJnPI3biSuXXuseflu5xbv2weAsWHD6u2kqHdk2q0QQgghhKge5gIwep/duT3uhPw06HUP6HRQnK3aP7kCWo+EK9+Cr6+H1L1ww5cQe5lKOOR7+gymdVnB339jbNwYY4SaclywZYvzWMs/N3Jw8BAsKSkAmBOPojVvjjUzi8xv5pHx8ScYmzTGq127Gum7qD8k+BRCCCGEENWjIAManmXdRE9/GP6ya3/oC7DCkYRl3xKIXwvmfBj3PbSsHxlaK5IwfgI6X19ab1VBpzUrC4Doue+g6XTE/vA9B/r0BSBv7VrSxlwPVisAgVdfRfiUKWgGCQ1E1ZJpt0IIIYQQonoUZKi1neejzwPwbJZr35yvpuLW08DTbreT9fPP5Cz7zdlWkjgIwFZQCIBnq9YAGEJC8O3XD4C0mbNcged119Lo1VcrrHkpRGWR4FMIIYQQQlS9/AwozISgmPO7XtPUf7cvdbXp6+9IXc6iRaQ88STHHn4Yu8VS5ritQJWV0fn6ONtiPnhfTWF28B86hLAHH6r6zgrhcN7Bp6ZpEZqm/VOZnRFCCCGEEHVUsuNrY6OuF3afJn0g6lK1XZBxYfe6iOVv3uzcthUVux2zWyyceFlNWdZ5u9bYajodsd9/B0CDe+4mes4cjBHh1dBbIZQLeVz0BnCWK8aFEEIIIUS9lrgJ0CCy84Xfa8gM+PxKaDXiwu91kSratdu1/e+/zm271UrRvn0q+RKgeXq6XefVrh1t4/ZWTyeFOMV5jXxqmjYIyAeOV253hBBCCCFEnfTvTxDRAbwCLvxesZfB9HS4ad6F3+siZLfbMcXHg14PwNFbb3Uei+vU2ZnVNmrObDRNK/ceQtSEcw4+NU3zAKYDT1R+d4QQQgghRJ1zfBdkHIQ2Iyvvnnqj2/rF+sSWm4vdbEbnVU7NVKuVvPXrATCGy5RaUbucz9/YJ4C5drs963QnaJp2l6ZpWzRN25KWlnb+vRNCCCGEEBe/7Y4RyrajarYfdYT52DEAQu+/n5BbJwDgN3AgfgMHAlB88CAAOh+f8m8gRA3R7Hb7uV2gaesAm2O3C/C93W6/43TnX3rppfYtpYrcCiGEEEKIOuzTkRDQCK77yNU2/xZIPwD3bT79deKsmE+kcnDAAAAaf/Ixvn36OI/ZTSbiOrnW1LZYtRJjo0bV3kdRL53V/O5zTjhkt9v7O99B09ZUFHgKIYQQQoh6JmGDei0dfGYnQWB0zfSnjokf4UqypHm55/7UPDzQfHywO8qsGCIjq7VvQpzJBRVHstvtl1dSP4QQQgghRF2SvF2Ndv7zpSqz0u22mu5RnVBSv9PQKBLvzp3KHC8JPKPeelOSDYlap/5W5hVCCCGEEFXngwHu+z4NaqYfdYTdbsdeVIQ+NBT/gQOJfOH5Cs/37devmnomxNmT4FMIIYQQQlS9c8wzIlwK//2XI9eNce7r/PxOe27Q9ddjOnIEvb9/dXRNiHMiwacQQgghhKgcJQGmzgA2i9rudCNkH4O+D9Zcvy5idpvNLfAE0HmXU2LF4UwjokLUJAk+hRBCCCFE5bAUq9dut8HfjoRDV70NBo8a69LFym61kjxlKv5Dh5Y9ZrbUQI+EuHASfAohhBBCiMpRnKNeQ1u72iTwPC/5G/8kZ/FichYvLnPMknqiBnokxIWT4FMIIYQQQlSO9W+p16DG8Ng+yE+v2f5cxHIWLXLbD58yBUtqKic/+wxrXn4N9UqICyPBpxBCCCGEODdF2WCzgk+Ie3tJsNmkN3gFgn/D6u9bHVG4a5fbfsgt47Dm55O1YAENbr+tZjolxAWS4FMIIYQQQpTPblf/6XTu7TM7qgD02SwoXUtS7wEBUSrwFBfEkpbm3A687lo0Dw8MHh603ra1BnslxIXRnfkUIYQQQog67s+5sH95Tfei9vnianipkXub1awCT4DngmDNq65jRVngFVR9/auj7DYbtrw8575HTOMa7I0QlUeCTyGEEELUbzYb/PYkzLu+pntS+xxeC5ZC9xqdKTvcz1nzEqTGweyuELcIwlojzp/dZsOcnOL2MzeENqjBHglReWTarRBCCCHqt6yEmu5B7Zd7HAIi1faR9WWPz+3p2u55d/X0qQ6yWyykzZpNxocfAhBy6wSKDxzAf9iwGu6ZEJVDgk8hhBBC1G9p+yjMMGIp0uFvt7uvYayvlj4Bm9917afFqeDTaobUPRAQDZfeDqtecL9u0HRo3Kt6+1pH2O124jp0dGsL+b+JGCPCa6hHQlQ+mXYrhBBCiPotbS9HVoSR9EcDMOVhTk3FkpFR072qOeZC98AT4PA6yM+AF0Jh53wIioH+j8OMbOh2uzpn2MuqTZwXu8lUps3QIKScMy9eJquJRfGLsJeexi3qFRn5FEIIIUT9lnvCuWkvyuVg/8EAtI3bW1M9qlkHV5ZtW/+m+q9ERAfXtoevevUNrdp+1XG2ggIA/AYOJG/1ajQPDzRD3fmqbrVZ6fZVNwAifCLo3rB7DfdI1AQZ+RRCCCFEnZb5zTfEdeyE6cgR7HY7hf/+y8nPP3ceN2dkOrdtr7ZzblsyM6mXkv5SJVMmbYYJv0DXCe7HNT30ud+13+cBGDgN2o+u3n7WMfaiIgD8Bg2k9fZ/aP7bshruUeX6M+VP53ZOcU4N9kTUJAk+hRBCCFGnpb39DnazmUPDR5D1/fccuW4MJ15+xTn1L293ivNca7Hrq1HSpEnV3tcasX0eZBxy7eelgV8EhLeBZpfDqNlw7Yeu4w9sgeCmrn3/hjBgCuiN1dThuslWqIJPnbcPOi8vjJGRNdyjymO1WTFZXdOK0wvTa7A3oibVnbF8IYQQQohyeDRuTKFjDWfGB64gKn74CHz79oXkbGebKdf11ajwn+1lb7bqRZV858avqq7D1clmg5/vVdszHD+HwkzwLlWrU9Og0w1wfCdsnAPBsdXfz3ogb80agDo11RYgKTeJET+OIMovytmWb8mvwR6JmlS3fruFEEIIIU5hiIhwbpsTE53bpoQETAkJBHQIdLYlrnOvp2jLy0aXuQ+iu6sgbN3r6oDFBAaPqu14dTDlubYtxWDwhPxU8A4ue+4VL8LQFyQbcBUp3LkTAM/WrWq4J5UrKS8JgGN5x5xthZbCmuqOqGESfAohhBCiTtOMFU8HtRaYy7SFd8kmdXsgKXeMJqrNVoi6FFJ2uE5I2QExdSBhiqnUCNSmdyHziPpsfR4o/3wJPKuMNT0d7y5d8IytWyPLZqv73y9vgzcF5oIa6o2oabLmUwghhBB11rHHJ5OzcGGF5+QfLkDTuwdVgU3VyEzOdsd60GNbMGXbSPwjGJsF+OcLNWX1Yld65PP3Z2Hrp2CzQOuRNdeneshut1O0bx+erVvXdFcqXckUW2+DNwA+Bh8KLBJ81lcSfAohhBCizsr97bcybRGXZBN+STZNBjmSntjBO9ZVT9EnrBjDvYvxbmDC6Gfh5H5fbFY4vjWQvGPeFKR6wrYvYOnk6voYp5dxCH66R9XmPB+nyzoa1e38+yTOWdHOndhyc/FqU7eCT6vNyvf7vwfg56t/Ztv4bXgbvGXabT0m026FEEIIUWfpfHywZmfj1SQMTy0Bm0UjpLUaiTHn653nNbiqL762WPzbh2M8vACiu+Phb6Eww4cT2wIxeFnL3vzvj2D4q6Cvwa9TK5+DPb/A3kXwZOK5T4vNPa5eu94K2xzlZ2IHgE5/+mtEpTo2ZQo5v6rRec/WbWq4N5VrU8omNqdspkODDkT6RqJpGj5GH5l2W49J8CmEEEKIOstWVETAyJFEDAzAsPVNt2MGH1dAaWzaGr8r/k/tXHYtALqIpnAkVd3HUiqoKx3f5SS5lx2pTPFrYOPbMPYbVxmTtP0q2267qxx9cUxiM+WqbLSRnc/tPbJVMhgGTYeIDiroPLWup6hSub8td257tW9XwZkXnxyTGll/vu/zaI4HIz4GH+fI529HfuOlzS/RJawLswbNqrF+iuoj026FEEIIUSeZkpKwFxejDwrC4Ot43l5qOqlm9ELvqQJQXVijMtfr/Xyc24XpHs4aoDknQmHAVOKXhZH4f+OqpvNWM3xxNRxcATvnu9rnj4MF4yHfMWU4M8F17P3+574ONTsR9J7gGwo974LuE6VeZzWyFRU5f0cjnnoSnadnTXepUhVZVO1SX6Ovs60k4dCHOz/k8bWPc7LoJH+m/FlTXRTVTIJPIYQQQtRJJTU98zasB2uxCrLuXAVXzVEnRHSg6dB0QjvkYIgqJ8Oo0du5mRXvS1GmKq2SHWfHFDGE4iwjeXtPVm6nf7wblkyBXd+72o7vdm1nOUrFnIwHux3SD0CPuyDMMV0zruLkSk52O8wIVHU7A6Mki20NKant2eCeuwmZUPdGnEsSC5UkGwLwMfqwM30ns/+ZzcjYkdzZ8U4KLYWYrKaa6qaoRhJ8CiGEEKLOsWRmgl2NAsa8844aSdQ76nKWlBdpfw0e0VGEdchD821Q9h65p/8yfOjaW10755vs51RWM+z8Fv56Hza/CwHRENpKbX99PZgKoCRRy8dD4dtxarpto65w70bwDISDv5/dexVlV06fxQWx5avfRf8hQ2q4J1WjZOTTy+DlbPMz+gGg1/Q83/d5ovyiAEgvTK/+DopqJ8GnEEIIIeqUnOXLOdC7D1nffU/AyJF4tmgBlmIwOILPrhNg+CvQ8x64ay2M+URNOz1Fg/5R+McUonlUnCLDnn0M1r0Ovz8HOxecf8dTdpba3gF+4a56mweWw0uR7ufvW6xe216p1mrG9FBZeP/5+szvlZPs2h7x+vn3WVwQW54qdaP396/hnlSNfHM+GhpeelfwGemnfo8DPALw1HsS5hMGwJd7vqyRPorqJcGnEEIIIWqV1LdmEn/tted8nSUjg5ylS8n8yhV8BVx5pdoomXYL4OELve5Vaxt9QqDDdeXezyPUj+i+mW5rP8tjX/8erHoR1r8JP94JcUvOue8AHNuiXgMbq9eT8SpQnnoErn7Hdd5N81zbj+0DT0fg0qC5ev1lknr9dCRs/bz89yoJPnvcBS3r5qhbbWY+kUrhrl2YT6iEVjpf3zNccXFKLUglzCfMmWwI4JKwSwDILM4EoEVQCwC+2vsVg78bXP2dFNVKst0KIYQQolbJeP99API2bMCvb9+zvu7YY49TsGmTW5tvv76qFubuH6Fhp3PryKCnwb8hrF4MlK2HGX7vLaS++xWW9Z/g4VfqwKKHodVw0J3jM/6CDECDh7bDrw9Cl7Gq3TsYLrkFfrlP7bcaAc+cBKvJbV0qA6bC5vcgsota05mwQf3X7dYyb0X2UfVaMrIqqo35xAkOjRiJvUCth9QFBKAZ6uZX8uP5x4n0dR+x7xPVh3s734u/h3po0sivEZtu3kSveb1ILUhl6eGlaGjoNB1XNL2iJrotqpCMfAohhBCiVrDb7W77iRPv4MTrZz8l9NTAs8m8eeg8PCDpbzAXwH/eOLcOeQdD/8nog4LcmqNmvkXbuL14NG8N4MyCC8BVb0PeCUj+p+z9jm1T9ThPpzALZrPRMAAAIABJREFUvALUFNpr3oGm/dyP37oQrv9cBbU6vXvgCWoUN7IzpGyHZU+4H1v1X5jZSa13zUmGLZ9AQJRaV1qP2c3mMr93lcmak0Ph9u3YTa71w3lr1joDT4DgG2+osvevaSn5KWWCT4BJXSYxvt14576v0ZeHuj4EwJR1U5i8bjKPrX2MrKKsauurqB4SfAohRHWx2aCgkjNjClFH2PLzOXBZf9Lffdet/eTHn2ArPHNCH1txsdt+g7vuwqermt5H7nH1ep71OCOfm+Hc9undi4DhwwEwRKr7WYt1Kugc/io0crzn0Y3uN7Fa4MOBqlRKeZK2qERDJcmQyhPbH9pfU3FnU3ao183vudoWPgzrXoOsBPhwMLzZFo7vgo5jzn109iJmt9s5+fXXpEx/BltBAceff4G4jp1InHjHed0v64cfOfHyy9jN5jLHbMXFpM2ezf4ePTly01hS33zLecyckgw6HY0//xyfXr1ocNdd5/2ZKpvNbiOzKLNS7lVgLiA5P5lo/7N7wHFHxzv45j/fuLUdzjlcKX0RtUf9+RdHCCFqUupe2DgLXouF1S+5H0s/ADvml3+dEPXEiVdexZqeTtqs2WWO5W/efMbrrVnuIySBo0sFaUVZoDPiPjf27Hl36ULDZ58BwBge7mzXh6ltS0hX6Doeet0DgY4v2n+86X6T9H2u7X++dq/HmXtcZa8FsFnOqW+2wkJSZ84ke7Ej+dCosj8/tn6qXiM6QHGp6cNdqqhGaS1VvP8AJ154kazvvmNf125kzlNrZ/M3biz3fFtxMVk//EDyU9M4NPI/FO3dC0DRnj3EX3U1KdOmcfLzLzgy9masOa6fq62wkH2du5A+9100oxFdYCAnP/uMnBUrADAnJqFvEIJvzx40+ezTWpVsaObWmfSf359cU+4Fjwj/dfwvLDYLPSN7nvU1HUI7cHv72537qQWpF9QHUfvUzQnmQghRmxRmwtxerv1Tp+O90xPsVuh0g9TaE/WS3WQi64cfTnvcnJh0xntY0lSZhohp07BmZuLRpEmpg8Vg8Drrv1+7j2Uz9sNNTOwXy8NDWgFgbNQIAN9Sa1D1wcEAWFuMcV3sHaTeKyAKdn4HzQeBbwP1AKrEL5NUXc7obrD5A1g6WbV3vEElGHIoiovDVliIzyWXnLavmfPmkfGeWiPr27Mnhm63wsIHyz/57nVqZHXLx9ByGIS1PqufR11xeMyYMm26wEA8mzVza7OcPIk+KIijt95G4fbtzvbEu+7Gu1s3cpctc7b5Dx9O7vLlHLisP/7DrsCank7+xj8B8Gzbltgff8CSmsrRW28j+dHHOOYYJfUbXPsS6yyJX8Kn/6oHFX2+6YNBMzCjzwyubnG185w5/8yhc1hn+kf3L/ceSblJHMs7RteIrqxJXIO3wZuu4V3PqR+PdHuEuzrdRe9venM056iz/bE1j9Evqh+jW44+j08nagsZ+RRCiKp2aLX7fn46/HAHbHCMUNit6tXiPm3wrFnNKrmIEBcpc2qaGgksLzjUNMxJZw4+zUcTAPDp0YOwBx9AKz2d1FIEBs+z6ovFauPKOevJLbIw8/cDFJrU30+/AQOI/eUXAq+6ynmuzs8PjMYyo660HgHZifDjHfB6M9g+D9Li1LF2ji/ymYfh+G5X4NlqOIx+H2IvA1Tgefia0SSMvdlt2rEpMZHsRYudo1L5GzY4jx3od5k6t/8U1fD4QZWYCFTCIp1erSnt9whEtDurn0dtYTOZyPj4Y8wpKed1vSUtDRyBX9u4vTRftpTmv6/At0cPig8coHDXbkyJiSTcMp4DffpyaMhQZ+AZPnkyjT/9BFtREbnLluHbty/hT0ylxdq1RM98i9B77sZeXEzOrwudgSdAzHvvoWkaxogIGs6Y4TY9N/LFFy7gp3H2fjn4C9M3TC93FDPXlEueSZV62ZOxh6l/THU7brFbWJ3o+v+XyWrig50fcN/K+077ftPWT+OO5Xdw/8r7WZGwgsGNB+NRUl/3LGmahp+HH1F+UezLVDMGzFYzyxOW88zGZ87pXqL2kZFPIYSoat/f7r5fkA7J22DXd9Brkqu9OBeMXpwTux0+HaFeb1t87tcLUQtYTqg1mf5DBpO74ncCrhpFzq8LAfCIjcV07MzBp+moGiHxiClnfZnFdNbB55p9aQAE+xjJLDDz15GTDGil6hB6tW7ldq6maRiCg7GcPGWNnG+Ymupb4ud7Xe2j34fD62DjHNAZwDsEHtiqkgWVUrBlq3O7cPt2fHv3BuDESy+Tt3o1Xu3bkbdmLfkb/yR43Dgyv1blZTI+/IiwB56Cy59QwSbAU8muMjMXqZLpspkLFhD+8MPkrV9PxNSp6AMCyj3flJRE4l1343dZP0yJSZgS1MOJZotVwiePpk0BCBw9mtwVK0i85x6sGRnO683JqhRNs6VL8IyNBaDxZ59SvG8/gaOvcSsdEvbgg4T830TyVq/CEBqKPjAQj9hYdN6uhFC+vXrSZu8eUqY9jf8VQzE4Rs2r2jMbn8Fmt5FVlMWcwXPcjo36aRQZRRm8efmbzN7mmq79fJ/nnUHeyqMrGbRgEAtGLeCH/a7ZCVabFX3J75fD7vTdbEvdBsDGZDWVeUDMgPPue6vgVvx25DeO5x/npX6u5SpWm5Un1z/Jja1vpFtENzKLMnlq/VOsP7ae1/q/xvCmw93+fKpakaUIL4P8v/dsSfAphBBVLbgpZB5R234RkOWaRsTMDq7tLZ/A5e5Pns/ojzdUJk+AuEUqyUirYdB/8oX0WIhqZT6ugk99SAMAdD6uupoeMTGYk46d8R6mhKMYwsPdrnU6i5HPzHwTf8ZnsC0hE0+Dju/u6c2QN9fx4qI9DHj09F+g9SEhWDPLCT5LaHrX7IbY/ipD7ahZsMAxvfaqOWUCTwDzMddnPnr7/wHQ6LVXyVu/HoDifftIffVVAPyHXYEhtAFps2ZjPnFcjSBrpQIDj4urhqTdYgG7nfQPPsCrfXusWVlkffcdAOaEoxx75FFAjWbGvPce+X/8Qd6GDYTdfz86Pz+yFizg+IznADgZH++8r9+QwXg2b+72Xv6DBhJ49dVk//ILoBJVhT/6CAVbt2JOTnEGngDe7dvj3b59uX3W+/kSOGpUhZ9L0zQavfTfc/xpXJgOoR3YmbaTNUlryDfn42tUvwt7M/aSUaSC7UfXPEq0XzQfDP2A3o3UQ46X/3qZGP8YDDoDezL28NbWt/j10K/O+/548Ef+OfEPo1uOpnvD7qw+upo3tqhs0pMvncyqxFU09G3I5dGXn3ff24S0YXXianak7WB5wnJn+5qkNSw9vJSlh5dyd6e7ySrOYv0x9fdiyropZBVnMbbN2PN+37M1e9tsdqXvYlPKJl7q9xKjmlf85y8UCT6FEKKqefqrunyjZsK61+Hvj1zHcktNIVvzEnS7Dfwj3K9P2w8ndkGH6yBhI6x/C4a/AqY82PKZ67wfJqrXpL+h573geX7JVYSobiVrOoNuuJ6s+fMJuu46sr5VSbiM0dEUbN2K3W6neN8+MufPp3DbP0T97w1ylizFb+BAvDt2wHT0KB6NG5f/BlbHms8KjJ67gSMZqvxF96bBhPmr8w+k5lV4nSEkBNORI9jtdo499DCG0FAajmjkOuHGr2DFM5BxAIa9rNraXa1qcualQpdbyr1v4fbteF9yCZqnp7OETPIU18OpYw8/AoBnq1b4XHopvj16UPD3FvLX/YEtPx+d78UVcJaWcOttFG51jfzqAgPRh4QQ8+EHHLnOtW4zf90fxLVzBYOZX89DHxDg9jCg4bPPoHl7EzhqFJrefaSuRNCNNwJ2gseOxbtLFwB8unWDbpX8wWpAcanlHL3mqdwDnUI7ERMQg4ZGI79GXN/qesa3G+82PfavcX85twctGOQMPKf3ms4PB37g+T+fB2Bh/EJGtxjNTwd/AqBvVF8mtJ/AhPautcvn64omV/Dp7k8pshYxb+88Z/vDqx92br+/U6137hXZi00p6u/JH0l/nFfwWWgpZEXCCkY1G3VWI6cf7vrQuf3U+qfoEtaFmIAYAOKz4rl12a0Mbzqckc1Gckn46ddt1zcSfAohRGVL2grLpsKg6dBsgJpO6+mvitW3GOoKPjuMgd3fQ4+7oe2V8PkoSP3XFXza7bBxtvriCmo0JW4xHFgOB38HuyNb5sBpsPqUp+lxi6DzTdXzeYW4QEV792Js3Bjv9u1pG6cS80S99SZ2kwnLyUxseXkUbt9O8uQpzvWf8VeqUYb0uXNps2snpoQE/AaUnwTFWWqlAiWBJ8B/OkYS4HV2X5F8evYk7a23MB87Ru5yNTrTcMyrrhM8fOC2RaoPpR8sDXyq3PvlLF1K7orfsWZn49myJY1ef42i3bsxHT5CyrRpbudqPj7E/vyTc32rR9Om5G/cSPITTxA9Z055t6/17FarW+AJYMvOpuGMGXi3b0/kyy/j0707xvAwEu+dhK2ggOCbx2I+lkzazJlYMzPxGzxYPQSY8exZBRE+XS9xleWpQ8xWM0dyjtAkoAkJOQnO9p3pO9mZvpMuYV34cuSXZ7xPWmGac1un6bin0z08uNqV1Kok8GwR1ILnej9Xaf1vEdyCv2/5m4dXP8zKoyvdjk3qMolBMYNYsG8BVruVJ3o8gU7T8fSGp9mRuuOc3qfQUsjYRWM5lH0IgEWHFmHUG3l70NsV/v4EegaSXZzNsKbD2Ji8kUfXPsrHwz7GU+/J1b+otd3f7vuWb/d9y5cjvqRLeJdz/AnUTRJ8CiFEZbGY1Bqrjwap/QUT4Jp3ITsJWgxRba0dSUWSt8Nlj6qyCpfcAgGOkZLUvSo7JsDJeFfgCbDqRUjcDJ4BgAbF2Wq9WP/J0PIK+GCAej2wXK0pk+BTXCSK9uzBq517ApyAESMAyF2lEp4kjL0ZXWAghkaRhN13HynTnnaeW/DPP1jT092mSKobZ6vZBkl/q+yyp2G22tz2r+oShaZp3NKrMUt2VRy4ejZXmVIPDRnqetvUYpzjrEYf9eDJv2GF9wGw5uQ4p5Tqg4LQ+fqi8/DAp2tXfLp2JfvXXynYvBm/yy/Ht3cvfC/r75ZYyaOFmlKau+L3i3b0s+jff53bzZYuoXDrVry7dMGzRQsAgkqV0Gn88Udu1wb8ZySaTocxKqp6OlvLHS84TrG1mCubXck7298hxCuEdwa/w9jFalQw0jfyrO4zqcsk5m6fyy1tb2FE7Ah8jb5svnkzOaYcViSs4LW/X2PWwFkMajyoSj7H072epnvD7tjsNl77+zUA7up4F3qdnum9p7ud2zKoJUsPL+Xp9U8zo88MDDoV6hzMPEixtZj2oWWnTa9IWOEMPAH+TFFJo/4+/jc9Inuw7PAyvt33LS/0fYEYfzWyabfbyTfnM7HDRB7u9jCrjq7iodUP0febvkzqPKnMe4xfOp4l1y5xXl+fSbZbIYSoDN/dBi+GwfOl1m4VZcG3Y1WAGVSq7EPnm2DEK+AXDjd8DpGdwDdUfUn97Sk4oGrBka9KRxDTCyI7q8ATVJ2+R3bDdR/D5ENqfVejLvBUCoxT66LY/jWYXRkyhaitrHl5mBMT8WrbFr4d5z4tHfBq7wpKbdnZBN9wI4HXXutMGANQ8Jda9+zT85R6guteV4l9AC4Zf9o+/HPUPVttiK+afujnaSS70MyXmxIwWWzlXYoxumyCo5RZpUaTvMuu5zyddEfJFFB1S08NHgNGDMcjNpagG24g5NZb8WzmHmwH3+R64FS0bx8XC2teHjaTCVAPIgBarFqJZ2wsQWPGOAPPM/GIianXgeeHOz+k0+edeHPrm1htVk7knwCgU1gn5gyaw8LRC+kQ2oEJ7SbQo2EP7uh0x1nd997O97Jzwk6m9pjqXDPqY/ShoW9Dxrcbz65bd1VZ4AkQ6h3KuLbjGN9uPMuvW86nwz4tk+yoxMhmI+kU2olfDv3CJV9eQsfPO/LTgZ8Y/etoblp8E0eyjzjPzS7OZk/GHpYdXkaIVwhTu7vnXFh8eDG5plwmr5vM1hNbGfnjSBbsWwCo+qMWm4UQL/X3u/Tnn7tjrnN7+/jtvHLZKwBsOb6F7OJsshzJyLKLs9mcchY1jG3WC665WpvIyKcQQpwLcxEUZEBgqS84Vgv8+5P7ecNfgZXPg9kxla/n3We+t86oXr8eA08mwSdXqP0hM2DfEkhxTCW6/ElVLqHjKTXrPByJVkJbq4L2Cx+G0e9J7VBRq5WszzME+8LeRWrKeHfXl2JDeLjb+YFXqfVYzRb+St7atSTd/wAnP/sMAOOej8BzpJrq3naUmgJfolfZ0YgSGw+lO7f9PF1fjXw89Fhtdqb/vBuzxcb/9Ystc60x2n0kwyM2FlNiCrYOjmSz5SQTKs+J117n5CefuLXpvNzXqQbfdJNbgHkqTaej+fLfOHTFMEzx8fh0Pbf6iqCS/eQsWULAiBFoRuO5X28yYcnKwnjKn9upshcuJP2duZiOHAHAt08fYj78gKwffkTz9sbQ8MwjxUIpMBfwxZ4veGf7OwB8uvtT9mfuZ8MxVYanRVALwn1cfx6Tu597QrrqzB5bkUi/SCL9Tj9iG+UXxZuXv8mQ74c420qXZ/nf1v8xZ5B6IPX42sfZlLKJGP8YOoV24pZ2t3Ak5wgtg1pyJOcI8+Lmse3ENrf7v7DpBXak7XCuge3TqI/z2Ng2Y/km7hvn/vejvkev0zMwZqCzHyV9uar5VSyOX4zVbqVDgw7sztjN9a2uZ1rPaWUC62/3fcvsbbNZPmY5gZ6B5/Tzqo1k5FMIIc6W1QKzOsNb7eDQKld7fmrZc1sMgYd3Q7PL4eq5Z1fmoTjbtf3jXaoIPECD5uCjsoCiM0Lv+yu+z6RNENYWdn6rsuEKUUud/OprDg1VD1l0BeVntD31S6+xkZqirhmN+A1Sow22PJUUSP/vZzDvBpV868VwOLoRgmPh/q2gO/1XnoSMAuczmnsGNHO2+3i4vgTmFVvKvVbv50vsz66HT2GPPoItL4/iTEfg5lXxl0W73U5c127OwNN/2DBabfmbBnfdReA1V1d4bXmMUVFoRiNFe+PO+VqAjA8/JHnKVDIXLCjbV7OZtLlzSf/gQ2wFBeVcDcf/+xIH+w+gKK7s+9vNZjI+/oTUWbNInjzFGXgC5G/cyL4ul1C0axd+lw9wr9MqKvTd/u+cgWdDXxW0bzi2AZ2m49nez7oFnvVBhG8ED17yIM/1ca0/ndBuAhM7TOSPpD9IL0ynwFzgTFCUmJuIryMj9NO9nubGNjcyts1YbHYbR3KOEOUXxZLRS3ikm0ryVTrrb/MgV/bkxy59jI+u+IgGXg0Y0ngIrUNaA2qU+NTptr8e+hWrIwv27ozdgPpznBc3j9nbZrM7fTe703eTVpBGSl4KNruNAI/yywpdbGTkUwghzlZ+KuQ51n/tXQjNBsK8G8HgyBB441fQuI8auWnQQo04Tvjl7O9/9Tvwx5tw8pAa6Zx2XJVlAOhwLez9Va0hPVMWW50OhjwL39wEWz6VsiuiVrHbbKTNmk3Q9WM48eKLznZdbklJDE0l2yoVdLb8cyMZ739A0A3Xu92rdIDi2y4CTZdc9g0nbXLWv80pMjNqznomXd6cgW3CCXdktE3OKqRb42DeH9+NAG/XaJ+nwXV/ve70Iz9ebdrQYu1asJixpKtRVKvJcW050wNtxcXoPNUDKdOhQ9gdgVzjzz/Ht2cPAMIffeS071cRTa/HbjaT+fXXBI+7Gc9mzc58kUNRXBxps1S9xxMvvEjW9z/g1aolQWPGkP/nJtLnuqYT5q78Hf9Bg2lw+22g16vpsnY7eavVGt3D14zG2KQxnk1jMaelYmzUiLzf3ZPGNP32G3J//x1j48bovH0o+Gsz+gYNCJ10+lFqUVaOKce5/VSPp5j6x1QKLYXc3+V+xrQaU8GVddedne4EoH90fwrNhUT5R7EzbScf7/6Yf9P/xWQzuZ2fVew+9T7aP5ow7zDSC9P55j/fEOwVzO3tb6dzWGfmx80HDca3He/2cMxT70nPyJ6svmF1mYdmC69ZyML4hRh0BtqGtGVb6jZCvULpE9WH3em7ifCJYMSPI5xrWktn0gVoHti81ow+XygJPoW4ANa8PEwJCRjCws44xUhc5E6dWrvlEzUCeeA3V5tvOPg2gG63nt97XHILdBkHu76HH++AtDho5MjAGNQY7lxV8fWltR4B0d2h4CTs/lGNwJ7l9D8hqlLR3r1kvP8+BX/95dauyyxZo2iHpC0Q0915zBAcTMQTp9TANRfBwoeIeWAIpg3fE9LqlMDzyrfUWmuja+rqgr8TScgoYOoPu/DzNLBrhhp1PZiax6A24TTwc5+hUDoQLTRZK/xcxgj1/wBbsSptYTWXP3KXu2oVSZPuI/aXX/Bq3YpcR7AG4BFdOesVg266kaxv55P0wINEvz2nbCKmU2R8/DEezZtTtPtft/bivXsp3ruX7F9cIz0+PXviP2QIqW+8QdGOnWTNn485uWzQH3DVKHIWLsKccBSMRor3qCzGgaNH49E4BgwGvDp3dpY2AQgcdeWFfOx6KSk3iZ1pO4n2i2bxtYvRaTr+GvcXu9J2uY3K1Veh3qHgeIbbNKApAEdyjnCiQK2HHdd2HF/v/Zp8U77bdTpNx8LRC8ksyiTYKxhQszC6RXSjW0TFNXjKCxL1Oj3XtHAlyyr9Z1Nyv8ujL2dN0hpuaHUDPx/82S1APp+p0rWVBJ9CXIDjzzxDzpKlALRYt1YC0Lps7auw7jX1ZfayR2HhQzCn1Hoq/0iVFOhCaRqEOpJrzLsRHtt3/ms2W49Q606/v13tj5rtCowLTsKmd6HvQ1IPVFQra6YaYSiOj3dr153cBUP/Tz0s2TATbvq64hsd3wk7v8UPoJWj7dKJ8J//qbXWHu7JeixWGy8u3uvczyu28MA3/7Bop6q1271p2Ycz/+kYSZuGAVz37kYKzhB8Oj+Hn/r7lP5vIIFNTWWOl/w/4/DVV9N66xbn1NOIZ6ZjaNSozPnnI3LGDHIWLcZ06BBH/28iLVeXfXBlKy5WWYbbtyf1ddf0fJ2PDy3WrmF/dzUCGzxuHJlff43m4UH0O+/g060rOh8fgq4dzf5+lzkDT6927fBs2wa7yUzE1CkYQkOJeOIJbPn56P39SXrgQXwvu4zQu+6slM8oYGXCSh5eo2pePtT1IXSa64FHx7CONdWtWivIKwiAN7a8QbPAZnQN78oTPZ6ge0R32jVoV+Z8X6OvM8FSdXil/ysUWgoJ9Q7l8e6Po9f06DQddrsdo/7c11/XVhJ8CnEBikutV7GkpknwWZdlHIDgpo61Y3oVfJbW8263EZYLEuKYJucdfGHJgqIudd9f+KAr+Nz9gwqmTXkw3FH4/sDvkJ0Il95+/u8pxBmUJBiyZWe7tes97BDbH3xC1e/my41h8kHXtHaA9AMQ0lxNLc846H5j72AY+Yb6O3NK4Gm321m7X9UqvLJTJP1bhTHl+53OwBOgXaOy66kMeh2tG/rj7aGn0Gwhx5TDzwd+Zny78aedAmdooNZn2zzD4Un3ZCWmI0fIWbTIuZ/x+eeYDh/Bq2NHQm6+udz7na+Ip54i5amn0Azlf9VLmT6dnF8X0uTrr9zaQyfdi97fnxbr1pK/YSP+Ay/HbrMSMn6CW3Zdna8vMe+/R9aC7wi9b1K5o6uGkBAIUUF9ky+/qMRPJwBWJaqHCq2CWzGxw8Qa7s3FJT473vkzG9xkcA33Rikd7HobvGu4N1VHgk8hLoBns+bOqUTWrKwznF2HrXweYnpCK0eCnOO7VZIc40X2j2dxripP4lfOQ4S8NAiIAr3jn8271qq6miXaVOJ0Ma9AdX+/iDOfW5FG5RRNNxWoUaETKsEBKTtV8qRmA+Hr61RbxzHg6X9h7y3EaVhS1XQ3zaBht7jKB+g9bWr2QEwvFXwWZ8MXV6t/S4Y+r0oXvV3yQEVTGZ91RrCZVdPjB06bVOiPA+lM/HwLAFOHt+FgWl6Zc6KCTv/vlY+Hnm/+SmRb4dskW/6kfWj700690/R6/IcOpTg+HrvBm7yVK/Hp1o2U6dPJXfE7oEYJi/bvJ322yroZ9sj5re+sSNC1o8lZsoT89euJv/oaGtwxkYBhw9A8PCjas4ecXxcCkP7BBwAEjx+PV9u2BF07GgBjeLizpmbks8+W+x6+PXrg26NHpfddnFmuKZeVR1fSs2FP3h78dp1ZD1jVejbsyebjqrzJJeHl/D9SVDlJJXYRKti2Dbup7FQeUQNK/WNf8jS/3slOgj/+pzJMFmbC5g/gvb7w8RWVc39LMXx1HczpBlmJlXPP8ljN8HI0zO3taju0CuZcCjMCIWE9BJbKVteoC9y+DB7Zo7Lahras3P406gIBZ1cA/LS8AuCa91TClTGOEg4n4+H15rD1M7WfsB6+HA3rSmXFfTlaTcsVogrkLF8O4Aw8PfxVFlnd6Flq1D8g0lVq5ehG+OdLlWwrsfQaUbvKBj3xN3hgG4z/CSqYlrY3xZWQJTrYm3aRrlHOP58cxKIH+hHs61HepQB4G1XSoMTcJHVN8p8VfkZDeDiW1FRyFi4k6b77iR91lTPwBGg6/1s8m6s1X8HjxtGgiqailgSSxfv2kTx5CnGdOpP3x3oSJ93nPCd/7ToAwu6/z3m+qFnbU7fzwKoHOFlU9t9hq82K1WZlbdJa8s35jG83Hi9DJc26qQc+vMKVyKdHpDw4qQky8nmRyd+0maO33Ubogw8QMmECej9Zq1VTsr7/npyFCzFERGA5cQJrZiZps+dgKyjA0DCCBrfdVtNdrB7ZpcojvNoU/B1rlo47RtSan0Ph6YQ/1RfI6FLTRb+7HQ46vrRteheGv3TBXS7XfkfioAJHvb/0gyooK61J74r3a6MuY9Wr1fHAqvRUxdBWkL5fba9+0f26Y1uh5dCq75+od4p27HTbb/z6eMPMAAAgAElEQVToMOx9JkOTJq7GYS/D3x+59ktPc386zX0qLqjR0dOwWG28vFSV/Vj0QD80TSPc35VYKDLQm8jAimdpNAryJu54LpquEID3d77P/Zfczy/bjxHgbWRga/fZEobwcGy5uWR8rB76WNLS3I5rRiORzz9H4fbtBI8//RTeCxUwciSmo0dJmznL2ZZ4pwp09cHB2K1WbDk56AMD0Qde/PUD64KPd33MzG0zAfjpwE9M7OiaTmuymhj+w3DSCtXvU6RvpFudSXFmmqYxc+BM7HZ7nZ7aWpvJyOdFxFZUxPHnVM2i9Nlz2H9p9zNccX4s6emk/u9NrKesxxHuUp6erjZ0OtDpMB09SvrcuZz87DNSX3kVu91e5pr8jRtJ//DDMu0XlfSDsGG2GolM2gJ5J9yP5yZDt9vU9pej4dcHzu6+Vgt8Ohw+Ggyr/gvfjoM9v8K+xa5zNr2jpo1Wth/vhvnjXPvHd8Hbp0ypG/EaXDK+8t+7uoQ4vpynlaq9N+JV9Wr0gRaOQLPXJNAZ4N+fq69v6Qcg8wgU5UDydji8DmylkrsUZcMbrWBWF3XcWn69RVH72c3mMm2G62fiUTrwBPfgsu1Vpz92Fr7bmgSaGb3PAdo3CiDuZBwnCk7QOMSHGy6NLvea1IJUMgoznPuXNlXZLu2lvjaZrCYe+nY7t3/6d9nPFBYGQPH+/fgPH+5sb/LlFzRfphIOeXfuTMitt1Z5PUuvjh3R+fvT4J67ablxA40/+Ziwxx6l6bffYMtRI8IeLVtUaR/EmWUUZlBoKeS9He/RJUxlAJ65bSYD5g/gqT+e4q+Uv7j393udgWeTgCZM6T6lTiWiqS6DGw9mSJMhNd2NektGPi8iJ7/8EtPhw25tdpMJzePc/kdcHrvdTtGePaT9703yN25UjXod4Q8/fMH3rqt0fn7Y8vKwpKRgjI4m8yv3pA2WNPcERJnzF3DcsW7Gf9Ag55Sri86vD6ipcKACxRK3LYHPRqrtjjfAkQ0qSc+2L8DoC5vfhdsWQ9N+5d93ZgfX9jpV54rDajoYo2ZDTjKsfQUWTICb5qkA6Xy/tMWvhRXT4daF4BkAcaUCXDRVa1PTw7D/Qvc7Xes8L2aefmpUetuXan/wM9C0v1pL12qEKuXyx/+g6wQ1Svr3RyqrbwUjSpXCXFRqHV8pAVGg6WD4K2CzuB5yfDBAJZXpIRkzL0a2fFXOQNPbsFt16Hx9T5sQh7vWgsETgmNhczf4/Vm44r/n9H4n8008+eMuPMOX4dFgA38m9+Du3+9Gp+nYMWXHaa8b/N1gdc4Edc6YrtG8tmwfGjbnOQt2uIJOi9WGQa/+PTqSns+fySZKCoj4dOuGJTUV09Gj+HSvmofGFfHr25fWf7umLBv69MG3jxoti/noI/JWryZ4XOUmOxLn5sVNLzJ/33yGNhlKkbWISV0mUWAp4Ou9X2O2mlkYr2pEllhy7RJi/GMquKMQtdc5f3PTNC1Q07SlmqYt1zTtJ03TLjzyEWeU/csvpP3vTefT1BLm1LTTXHFuinbu5Mh1Y1yBJ5Dx3vvsbdceU9Ixsn78CfOxYxXcoR5yBD5Rb72J36CBABgaudboZX7zjXPbmpPjDDwBig8dqqZOVjKLyRV4+p6SlKdxb7jlR7juY2jaF4aUSlCx+V31+st9lGvlC5CbAnpPmLTZde9ixzqtTje4MrAe3wVvtoHng+GT4WCzlX/Piqx5BVJ2wLyb4IPLwZSrAubONwN2+PdH6D0Jet1bNwLPEiHNICdJJSLqdJP6bH0fgrBWKlPvoGkQFAMdr1fnz+nqPgJZWex2WP60SiazYWbZ4wOegJxjKvPu/HHw3a1q5Nboo44veRxS48peJ6qGqaDSfg9sOWpau95DzQwJnlDBbIJGXSC8rfrd7PcwzMiGPvef0/s99eMuAKLD1LTzu3+/W/XDXvbfjQJzAXmmPMxWs/McsyOZUXiAF7f2bozOM53eDVWisVd33QOaum9yVhEAn204zOVvrOGDf11rTHU+3jT54nNarPyd2savX18aTn8az2bNaror9Zbdbmf+vvkArEhYQbPAZvRu1JvBjQfzybBPmNZrmvPcG1vfyMQOE4n2K3/EXoiLwfl8qxoHvGm321domvYuMBz49QzXiAtgt9lInvoEAOFTppA82VVo1pJ64ryLUtstFnJXrSL7hx+xFaipjIaGDYl8bgZ5a9eROW8e2GykzZql1jY2iqTlqnMocl+HmVNSsOXkEPHkE//P3nmHR1G1bfy3u9nNpvcQSE8ILXRD79IEBGlSBQQp9oLyitiw4AsCvorYRQWlKL13AUF6ryEJ6b1nUzZb5/vjhN0sSWjCZ8t9XXslM3PmTNnZmXnOcz/3jWu/fijr1UMVHIz70KGYS0tJe2k6Jfv2A6AKCKiSsc7//geQyXDt/TepqTObRQB5vfbykc9E8HJkMZxcAuE9RTBev1ImtPFA8bL4WXvIqfDW825o229xFixsYF027YBQyJ0RC8e/EUFG91lintIBHnwDfq1Um5h8BDLOgn9rbhunf7QG0MnWwRYC2kDkEDi3Qky3e+r2+/y7wCtcCAyFdgW3m9w3AiqJMOTFgU/DmtveDQqT4bBQ+SR+v/g7aSfsfgsGfSq2l3nBlnL90Fwh6rSoIp+0egI8c+ze7te/Ged/EfXWkTfUOUsSLGolrp3Ht/4x6x9AKswGwHNQD2ThnfEYM/oP9XczxOeUsPtKFv7uDgR6y8jOtl3+3cXvmNR0EgBao5ZBGwbhZu/GnM7W7OprB19jQTchxnXZ8AMAmiKrCrVLo7fQpo0mKb8tgZ4OzN58GYCCSmrRMrUamZ1dzRneWvyjYZbM5JfnY5bMuNu7o1Ko0Bq1rItdR1u/tnxz3rYU55Men9hMN/JsxPpB67mQe4HB9QfXqtrW4m+PO74TSpL0eaVJHyC7pra1uDeQtELgwG3oUNwGPkzpoUMUbdwIgDEz8677zV/2I9kffmiZlru5UX/fr8hkMhxathTBJ6C7JgRKjOkZSCYTMoXirrf5T0Hh+vUAOHcTI+AOLVrg0KIFAHIHB+z8/Cg7cQJdtDU749C6NfXmzSVx+KNoz5wh7bkzuEZfqdr5Xw1512D5cKGSCkJAqOVY8RLa+UWRObsZhn4N2ZfhwmpRD1oZ+yuJB/Wfb2vN0nZKVWpl5+lw7mdB53ULFJmxrdNh6LdQmAQnlghj+uoezr8tgKvbwFF48PHMcfisIsgat0HQgRVK6PKK8PG8WXD2d0Xvd0X9ZNupN28nl8PE7fB9P5GBvNfBZ2mu7fTARRDUHp7YZZ336PeQ9LtV9Kl+L7Ffw7+DNZNAX3pv9+nfiCOfw++fVFgMVZzPlOPw4JviN6R0gNhdUJIpPuufhKFfiZrb9DNieZ3IOwpITXnCV1MZHILrzbKefxBms8Rj3x5DIZPx09RmDNp8HBkyJETG1U5mx8enPmZCkwko5ArWxKwhqyyLrLIsXtpntT3ZmbiTviF96R3cm+hScX3GZGnQG7ogV6di55SAg/9K1p7qZxEtUipkaOytPqNyda0S6b8V8YXxTNw50Ua11lnpTImhqtXPvhH78Hbwrraf+h71qe9RW5dbi38G7noYTiaTdQA8JEk6eg/3pxbV4HpWUt00EoB68+biO/NVYjt0xJB197G/9ryt4qC6YUPLiJqiIhCN6/GgxccSIGHIUPw/+bhaM+l/E7Rnz2IfEYEqJKTa5WZtVVEcZYA/qsBAXPr0oXD1agAK166j7PhxQKLevHn3cY9vgcIUuLxBZPsq00yjt8GqGzITgz61fdm81Ytn3ebikx8PB+bB0kEiKypJVrsPgOBOt95PuQKeOwnFmeDiBx8EiJfg7/qIoMpshJRjIpCpjF1vwuFF1unO00VAFdAGPEIgvId1Wc83b70ff1c4uMOIpbfX1sVP/C1KE9/VtleEl2nlc3W3yIsVf8N7QveZEFiN3L2dvRjoePQH8Kpvre9tOgxST8Gp76uuY9SLOtF/ElX6fuH4N7Dztarzj34uPgAzrokBABCU7fOrhJ1ScbrITAO4Bog64W7/EfcCs0n8Tisju+IZ4tuY8jMiW23f4v5aHHx9MJ70onLq+zpzKvcAAP7O/szuOBuT2USCJoG5x+eyOmY1bf3acj7H+jxMLRF2KtuGbqP/uv5M3z+dEQ1GWJYXZEYhmZwZ2KIegeF7+PHKMjZeiGHDWTG49uMT7Rj1tfXVqFRuxFCej6fa874ecy3+/2GWzBxOP0x99/r4OflxJvsM7x55lyCXIHoF9+KjUx9hMBsY2XCkhVp7PfDsVK8TEhJu9m7M7jAbx+tlBbWoxT8cd/WElslknsCnwLAalk8FpgIEBQXd9c7VQtQK5n3/AwByR+uNSeHujkytxpCaelf96hISKN6xAxAZOe3p0ygDbGsIFJ5VH5S6mBgK16yhTiXq778NkiRRfuGipc6zOniMHAVmiZJKNOXr4kPe4wZbgs+M1621HH9q8Hld7GfXGyIjeOhjcPQUtFq1G4R0gYf+K0Rp7hbNR4rgM+GA+FxH/wVCPOhOAobrgVFIZ4jZDmVWVUoO/U9k+DxCBWX01/dExlOuFDWcmnTo+opo+8Tuuz+efzrcg4VQVOYFEeid+FZ8pv0mbC8C2ohs9cnvYctL8PD/rHW5t0L6WVG/OeaXW3/vN9JAAZy8wFAm/Fen7hc1rJIE3z4o6oXHrbvTo/334UyF8NSgT4WImJ0a/JoJAa5re8Wy+RViU37NYOwaWNgQYissiWQKGLAALq4TDIYrmyDrorX/Rz6DVo9BaR583l78/t7MwXRR9K1s1K7a3copy6HUUEpKcQpLLy3ly95fYie/s1eVNzdc5MejSQB8PLIlK+LFvXXlgJW4q90BKNQVAjDn2Bzs5HZIkoRaoabcJGo3pzSbYlNX90vML5b/JZMzUcEefDq6FScyjfx4ZRl2rhcw6z1Qup3hYmkm4Gdp//LR1zifbODChAt3dBwA5QYT13JKaFLXFZlMRkGpHjcHO/J1+TZZstSCMvzdHWopmXeIMkMZl/Iu0cbvzoSgJEli5JaRXMmvnr0UVxjHryni+f9lry/p5N+JN9q/AcDCkwtRKVQ81+o2leBrUYt/GO44+KwQGFoNvCZJUlJ1bSRJ+hr4GiAqKqqq30Qtbgvas2dJHGXNOskdrMGnTCbDc9w48r75BseoB3Dt1++O+i5cswaA4BUr0F2NRnv6dBX1Vbm91Qct4shhFG5uJI4aTcmevdSZMQNTSSkl+/bh2r/fv4qKW3bsGKaCAhyat6ixjXOXzjh36Yzh6GoUW6ZQlOiA26THAFCu6EH4MG/K2iwkY6Y183CvlIsrI2/JEgzpGfi9+UbNjW60rfjshozEmF+qZhLvBl7hENgeUo7C2LXi5Veu+GOqpYM/FwHmkkq1szE7xEflIoSErmP0yqq+lbUvajVDrhAZ67PLBcUZQOUsRIK0BSLj3P4p2FKhiL3lxZqDT0kSn+vZS20BOHnffYbSodLA2NfdRXCUWenF/qMmMGgRhHb/e2VBdcVQkm2rMJxyHPZ9ILL6IAR4+s//Y9sxm4TgVtNhgkJfkAStxwkWAEDCQTi3Cs5WKHh3fkkM+Az+AjZU1EJ3eh6iJkHrCSIovR54Xv/dXRcXK68Q3jEbYM1EzAVZoHBD5milpV6HJEn0WtPLRgwoozTjjlQ9913NtgSeyye3o46Hns3xm+kX2s8SeAJ0qGf16DVWnNtpzabx+dnPae7TnOdbPw/A5GaT+faC1W9UoReWMPKKe0djz8YAqP02Wtp8de4qI9ouggq3ogKlHpBRbixHbXdzCq7OpEMuk6OUK9EbzQz5djUxOdmYyqzXRN/2sRwuWsKWIVsIdg3m5xPJvLr2Ag5KBefe7oPK7u/vorcudh0F5QWWmtwCXQFlhjL8nf3/cICdX57PT5d/wsvBi7nH5wLwStQrTIicUKVtrjaXmPwYMkozWHByAU29mxLhEcGJzBNE54uymvFNxlPHsQ4br23E19GXuV3mcjDtIJviNjG52WTa1rV9pr4c9fIf2v9a1OLvjrt5Kj8BtAZel8lkrwNfSJL0873drVoA5P9oa90hs7MN8LyemEThhvUUrl59x8Fn+cVLqJs2xbF1K9QNG4BMhvuwqols31dexr5BA+w8hMeZU/v25H33HZLRSO7ixeT/8APpM2YQvmc3qoB/vvqaMTeXtBkzUIWE4DpgwC3bK4svgp2ER/0ySN4HbkJFVKXMRdmvD6a8fEwF+eR9uwRjbi7KevVue1/KTp9G0ulw6tChyjKzTodmyxay5wuhjGqDz8wLwqfTtaK2scVoOLfSts3E7fcm8LyOJ3Za/4+4Bx5bjp7g2BYaDoDEQ9DhGWsdaaP+Yl7XGRAQJQKUWtwZvBtA8hFKL10jPzmCeou/RvFDpYz/6WW27Y06QZe9EStGCurl2NWC7qzNBwePu9+vhv2tQS/YBp4g6lR/Giau6SFf3v12/r/x4xBIPQFP7IHAikzM5Y0Qv8/aJvHgHw8+z1c8su3UYpDhRqp5aBfxaTkGyguhUcW9ruUYcU6LM8G5QnRHroDRq+CXCTB8ichCn/kRtr4Mm18UQed1XFqPyeCGwtW12gDi1+Rfq6jQ9l/Xn34h/ZjTZQ5K+a39DL87lIC/uwM7X+xCUkkM808KmvnAsIE27TzUHqweuBp3e3em75/OhdwLjG44mhDXEFr4WAcWb8y6zun4Ec9ci7WMozirnGnr15bjmcdRyVzo4P8AB9N+44LBKo+hqRg3js6PpqVvS26GqJ+iaOPXhu/6fse2C+mkOs7BMRiKr7wPMjNIcn5L34edE3x1+Bh9wxx5de15ZIoStAYXGryxnWOzelLH9e9bZxpfGM/bh4Va+raEbSQUJVhUh+UyOTuG7qCuc13Mkhm5TI4kSWSWZlKgK6CxZ2NkMhllhjLUdmpkyGyuNb1Jz9CNQ8krz7PZ5sHUgzbBZ4m+hN9Sf2PByQUWX81wt3BytbkczTiKu707s9rNYmTDkchl4mIYHznesv7DYQ/zcNjD9+cE/Q1RbjDx1E+nMEnwvxEt8HKu5jlRi38N7kZw6Avgi/uwL7W4AcasLMv/jh3a2wQZJToj53KNeOblU5pzBFNREQo3N5v1zTodhWvXYufphetDfS3zC37+hbJjx/AYI3y95E5OeIwaVe0+eE2ebDPt1LEjSGYknQ5DRoZlftG6dXhOmoTC2fnuD/hvgIw33sSsKSbo229ROFcdua+C9DOiXi0vDjY8KT4VkCUfxuuJSWh2C+pn3IM98RgzGr+33qrSjWQ0Iun1Fuq1ISubpDFjAWh45jRyB6tQT8mBA6Q88ywYrRnNos2bcYyKQnvuPC59+4iH8coxUJRs3ciAj0DlJCiRPV4T1haef5Pa3pE/gskA0Vus84Z8VZvZ/KNo/xScXkraIU9M+lLytxzBZ+AiOPoF5MYIijMIReL9Hwhf1huzy/pSK1Xz83aCZp12CkK73f1+udQRSsrxB2DZIDFv2BKxrYjeYv8OLxKDKb1mW2naf3WkVvhGLukF/0kQgys3ijOBuNb/iLH89WC997s3bxdSTR22TAaudW3nBUTB9EvW6TaTIekIXFxj00xyDaTcvhF23vpqN/f5uc+rnb89cTv9w/rTPbD7TXe3qMzAkWt5TOkaxp7Urbz5uwiqpzWfRpeALlXaN/JsBMDSfktJKkrCXe1Ov1DbgdzRjUYjQ0ZLn5Y4Kh0xaX2AWPzdrUykJX2XoDVqcbAT9+FV0auYc2wOMV7eNMjLRetoB5g4l3PulsEnwInME+xN2sv2a1ZNB5fGb6CU22Mw6yzzNme9x8aUz3Gqb0KuLEQqi6Asqy+7LmUyrkPILbfzZ0KSpBozmLuSrMJjMQUxKOVKIr0iuZR3CbNkps/aPgwKH8SW+C1VBitcVC5ojVpLNlslV6E3i+ttSrMp7EneQ155Hj0Ce9ChXgeCXILYHL+ZrfFbaba0Gb2CepFSnEJ8UTwGswF3e3dGNxpNuFs4/cP646JywSyZkSQJxY21zf9wmM0SMhl3nHku0xuZuuwUh+LEvazdB3uZ0DGEGX0bolb+u85hLQT+Rnykfx+MhQU4deqEy0N9cR8+HJlMRramnAnfn+BKhqAybQ0ORZ5wDe25czh37WqzfuLwR9HFCmEPlyuXkclklB45YvGbdOl955knp/bt0J49w9UHhCm8Q6tWaM+cIffzLyhcv4GIfffGisWYk0Pa9JdxHzUSh8jIGoV9/j9hLCigZP9+PCeMR93wNtU/S3NF9sikF/YSILINxnJRqxjRC4cmTSzNC1aspM7MmVXotxmzZ1O0Zi0BX3yOY5s2FP68yrLMkJGJfZgIEiWTiaz5820CT4D0Gf+x/B/y8yqhzKu/QW1P5QgDFt7ecf3VIFeIz3Wrl/q9agPPewHfxhR3XotplahNyv3sM+wjPsb1maMi67npOZGF7PicCESjtwgbF7lSUGyNevjhBobAtop621aP/fH9C+0qMveeYdBsuHV+n/cgrJvIfp5dAV2m//Ft3S9IkqiXvDEzn3wEtIViACugLTyyWATb22cIKquT191vM+Mc+D8gqM/3C44V1OgGD8HQb+Dqdsry3Sj/+iXqvv9eleYavYaYghj6hfZje8L2KsvjCuNuGXxuOp+OSVZComwJP/0uNA3UCrWFulkTlHJljUqinmpPnm75tGVakiQ+HN6c/s1sA/DrgSfA0IihzD+xgPcG+7G44bvYl7yO3lDMhdwLnMo6hVqhJtI70mZ9s2QmQ2NVcH5xv8jsyyQlCoWE0WykhU8zTmadtFlPrrJm8GSOsTiFxrIrwZHH2gf/Zes/18Ss4Z0j7+CidAEZvNDqBZxUThzPOE62NpvDaYcJcgliYPhAmng1oYt/F2QyGUW6IhKKEhi3fRybrm3CS+2F3qynR2APWvi0IKssi58u/2QJPBt5NkJv0hNfJJTal1xcgpPSiZENRzKr3SxLxjLQJZDcslyOZR5jT7KwExvfZDy9gnvR3Lt5lSBTLpPDX/PU3hIGkxk7uQyzBAp51YMo0hqwk8tQKxXsvZJFeqGWBxvVYfnxJFYcTaZTfW88nFT0aOhDn8ibD+pdTtew+lQK3/+eCMATnUPxclbx4Y6rLDmUQLcGPnRt4HPTPmrxz0Rt8PkXhqmgEMfWD+Dx6KOWebM3X7IEngDHXpxLhxceJWXqNGRqNQGffIxzt24Y8/IsgSdAdOMmeD/3LAUrV6EKDyd09S82AkY3QpIkkvPLcFAq8HVVk1uiQy6T4emkwlxqfUC6DRqIunEjClasxJiRgUmjQeHqenfHW1xM2kvTcWjVEmNWNmUnTlB2QmQCQtauwSEy8hY93DuYNBqyPvwQn6eeQunvjyE9nbgHRWCjDLwD0R1tPvi3gsl7YUGEeBEbvQpWjYUzP0GP11H6+1P/wAGSH38cfUICGW+9Td3/fmB5cTCXllK0Zi0AqU89jc9LL6G9aBX20P26HNX+3ylv9ha65Az0cdfwe/stSn7/He+pUzGXl5P28suY8vLBbEafnIK6UX1k2nzx4q5Jg5E/Vbf3fz84eIiMWC3uGYr37wfA7ZFB6JNTSJ8xAztvLxwfGC/ozteDILcAoV58XcH46aNCoCj9DHR4FnybCPpoWR4YyiHsHqjmymTw3CkhWHUj6vcS9YeF1UoT/HUQvQV+sdL16P2u8Dvd+ToUVPgDuwUJunK28JBkQQSM3yCC71vBZIR1k8UAgUwhspFJv0P7Z+79sVRGYDs4/rWoF1W7QouRlP7vY1AocO3f39JMkiQGbRhEZ//OACh1LYgo7073ZvBN7KsVx+DMibQrTK6GOV9cbiCnWIevq5qP91zFucF7HKpwIOvi34XPe1WfTb1byGQyRkTdvAZVpVDxYMBD7DBv5Jy3M6WF4pm5M3EnOxMFC+Ddju/SwLMBkV6R5Gnz6LOmjyVDp8/vADIzKo9jyGQyNg3eiEKmoJ5zPb4/uY+PLj3P6IgnCFK342Tmafo2DqNfaD8OpR3iqT1PcdbwIc2Xfcj58ef/MgGowWwgszSTK3lXeOfIOwAUG0RN/vvHrN7N/s7+dPLvxOvtXifAxbaUx83ejZa+LVk5YCVuKjcCXat+DxMjJ6Iz6fByqDo4ozfpkSFDeQNrIMg1iG/7irreJI24XwS7Bv+Bo/1robjcwCd7YjmWkE90pgYZMsySRPMAN5r6u+GqVpKUX8aZ5AJSC7RV1r/uXevjYs+OS+LHtfJ4MiumtKNjuBjAMpsl5JWC2S8PXGPu9uiKQFbOuPbBvD6gCWazhIu9HW9uvERcdokl+DSYzJQbTLiolTb/1+Kfidrg8y8KyWzGVFiIwsNaF5WQW8q2C1ZfT5VCzrHscnpERVF+8iRSeTma3btx7taN9FdnVukz99PFyOztCfpuyU0DT4PJzFM/nWLPFUH5+WJsa55afhp3RyXdGvjwpKcY7XJ/5llOtXgQTYPORB49jjn+GjFt2+H/0UJc+vUDs6DDaLZtR92kcRVBoxsR17MXZo2G0kOHqizLnr+A4B+qsVa4T9Bs30HRmrUU79qNfWgoxjwxumzfqNHtZ4wlCcryhTiKsy+8VWAVXOn4LFzdCitHQ6/ZKJ19CV23lqutWlO0YQOqkGBK9u1H4eVlUcx1CPNCG5+HZts2dFev4tq/P9pLF0lbsBylkxFDqXV0323oUDxGW8WqIvbtw1xcwLVefUifMYP0GQD1cO3cjHrfXPrLvKDU4q8HU34B9g0bUm/ePEyFhSQMf5TkyVNoePIEssrZtxuFVFaMsGb7u88EexdoNfbe72Blb9gb4V1f2Aj9lZF1yXa6+SgRfF4PPMN7Wn1ZGw4QqtHnf4alA8HZT2QvJ+0Q57c6FKXApfXiUxnV2dvcSzQdJpgIlWp7yy+cR5iplFkAACAASURBVN2wITuzDvDawdf4rOdnBLoEkqhJJFGTCMDKgzrMeonTCeAU4YTcrhSj1o9LOXFVNnEuLZVHV87HpA3BQ94EjepXrl+FjT0b80LrW3gQ30c8EjGAHckbic2PxyyZbaw2AN46LMorvu79NUsvL7UEnoaiFuhy+tA1oi5nOEZ91cM2gksTo3owMcpa4/wY1nKczv6dGeT3BpsyRTB3JOMIHet1vO19nnVwFk28mvBYkz/GStCZdGyM28jRjKOUGcosgWdysbgfNPdpzsTIiSQXJzOk/hC2xm9FIVfQ0qcljb0a37L/pt5Na1zmrHLGmerLf1QKwShKLShjy/kMBraoh7+77f3jboLOUp0RJ3vr67TeaCZLU45SISejSEvzAHdOJuaz4WwaTf3dGNM26L48c8sNJpYdSUSpkOPjYk+fJn4cS8hj3JLjALQP86R9mBdKhZyU/DIyiso5k1KIJIGfq5oHgj0Y3TaI9EIthVoDvRvXwd1RyeFrebQOcqdvpB+7L2fx6a9xXEgrYsw3x2y2/0CwB3klOhLzhNVcr8Z1mD+8OR5OViaXXC7jsfbBzN95ldhswb7KLdEx8NNDZBSVM6VLKN8cTMBBqWBIa3+6N7h1hrUWfz/UBp9/UZiLi8FkQuEh1PkkSaLHgv02bdqGerLzUhYd3CNoh6DiFK1Zi9fjj1sCuIgjh8lZtIjClYKm6dS5M+oGDW667SWHEiyBJ8BTy08DUFhmYOPZdDICg/hh5QrmJyn4fpnYblSd7rwXfw2AtOkv4xV9leI9e9DHx1v6ce7eHe9nn8WhadUMprmsDLNGU2U+AAoFZUePkjb9ZbyfeZqy48dRN26MQ8tb187cLUoOCCsQs0aD9tw5AAK/+QbnLp1vr4NDH4NOAyadlX4mr6RAGNxRUOlSjsL3D4FbEPKXLuAU1YLSk+fI+fgTAGRqNXbuThgLSwlofonELG90V68C4DVlMkRvIeG17zCU2v6UKysVYzYh+/UdFEc/p25rBakHrQGD5tB5vK5exZiXh0PTplXqhgHyly4l679zCd2wHnWjRrd3/LX4x8CYnY3CUwQQCnd3nLt2pWDFCnRxcbb08yFfCJrr6FXw2wIxuALC8qamwOh+wy0QcqL/nG3fLtLPWv9vOw0cvQRt2WwQ2eHKtjF2Khj6tciO7pgJSYeFymz8fuGdWx0q14yGdBHZ4vwECOt+Hw6mEmSyKqJShoxM7Bs04JsL32CSTMQUxNhYVajM9SjW+6CQyzCZJcoSn0Ym1xEUdIU8825m/fYuc7q8yc+nYvnfsR8xKOOw9xEsEK3REbVdGYEuQax6eCWuqrtj4NwrBLoK8bgt0adR+kBdx2DCy//LCz0jcHIq4oldTwAwdbcYWNAXtMFQ0J5Phw2keYAbAR4OrD61kY7hd/bi/XS7QaxYWI5z/QVM2z2NtYPW0sDj5s98gPeOvMfm+M1sjt/MvBPzaODRgBJ9Ceml6QS7BhPmFsa5nHP0COyBq8qVBp4NMJlNyGVyBoQNQC6TYzAZOJdzjneOvGMZTFDIFJgkE0q5EnuFPVOaTWFEwxF4qK3Xxh8Ndm8HqQVlxGaV8MvJFLZfFIP4c7dH06SuK/8d2owWge636MEW2cXlLDmYwI9HkyjTm3CxtyPUxwm1UsGVdA3FOmMNa6YQm1XC2wOb3HUAqjeaic7UcC6lkMS8MgpK9RyJzyNTU45Ug7/EgOZ1+WxM6yrzjSYzmnIjHo7KGvene0Nfy/99Iv3oE+nH0fg8Np1L51xKIZfSxbvbqaQCS7tJnUJ5fUDjaqm9MpmM1sEenEjMZ8fFDN7ZfJmMImFx9M1BMeimNZhYcSyZFceSOfRqDwI8RMIktaAMTycVjqrqwxejyczxhHyCvBwt69TirweZVNOVeo8QFRUlnTx58tYNa2GD8qtXSXhkMP4fLcS1f3+eWX6arReEwM/hmQ8il8ko1RvpufAA4YVpLN7/P8u69o0bY0hOJnznDuy8vZGMRgrXrUOzaTN+78yuMQN55Foe3x6MZ290Nl0ivAnydGT5MTFS+XjHELI05ZxPLSK3RMd7jzTlP2vPI5eB+folJEls3yj8P1XBweiTrHQ399Gj0Gzbjp27O+E7d1Q6zhgShw/HzsdHUFtnziNDL8M7PZFsexe6LZ2H78xXyZ4rfNoUHh6YCsQNrnF09f5afxTlV6+SMHgI1+/iqtBQHFq0oN7c/95y3ezicmJXz6ZTciVNroGL4IGqEu4kHrKth2s9AdOxZcSsFbVESj8vwoZJyBUSZIvsSOE1R/LjHAl4ZgCqpu0xr3mK+O2+mM1KAod4oCq/hMm3DarxX4n9V6gg/5qwx6iAucFgci/aYxfZjaz33rfZJe/nnsX76aeRyWTo4hMoXLOG/O++Ewvt7PAYNQrPCeNRBd6+9UEt/h7I/uQTMXg1ZQq62Fh8XnwBfVIySWPG4DVlCr4vi7rJstNnSBozBvfRo5CrHajz6n+qdmY2Cy9Xs0mIVnndnPVw37DzdTj2JbyeCXnXBHX1r5TlL8kWFFoQg1ETtwkhoa97QPppkeUc+nXN6+fGwuIoEayO3yCCfskkhJ9AsC60+eL/sWuqikH9P8KQlkZcz154jB/HlMZHSNQkMqLBCBv/zNL4F5jZswfNA9wZ9fVRy/x3hwYy/4rImj/sO4st2R/UuJ0jo4/grPrzhe/KjeW0WW71jvTWjichUdT3v/VwE/635zLTh+jI1sViLn6Ar3brmDOkKWPb/XG6Z4t3dlGqPIaDv/XcTm42ucZMcJmhjHYrqvddvR3Ud6+PRqchW2sdtPZSe7F5yGaclE4YzUYUMsX/q0CP3mhGqRC/9U3n0nlhlXWQx9/dAX93B44n5lvmnXmzN0VaA0GejuhNZv63O4bUAi0TO4UQFeLJ1cxifo3Opp67mtQCLZ/sjUVvFOyuJnVdic0uxmCyfZ/u1dgXO7mcHZcyebJbOAOa1eXDndEcjM2lQ5gXQ1r74+tiT/swrxqFd45cy+NIfB7twzw5ei2PjefSSarILFaGyk7OqDaBdG/og51czsJdVzmXWsRT3cMZ3yEYV7XSJjt7r2A0mSnRGSkoE/T3qGAPSvXGW1Jm399ymW8PiUCzkZ8Lc4Y048i1XPQmieGtA3BzVLLtQgavrRNZ/t5N6vBQpB8vrz5HVLAHq58UGf/rAfOuS5ks3hfH+VRRdtPU35WlE9vWqur+/+O2HrC1wedfFNezTfNGvM1+vcga+LjYs/+V7jY3kLDXtmI2S+wPz0YVH0vRBmEs5tK7NwGfLrrpNiRJYu6OaC6na5jQIYRX1pzDTi6ndZA7M/o2JMjLkcZv7uBp9U6eH94HlVcwGzI8efFn60388MwHydKUs/dKNnmlOn7dd5a+SccZHbPX0kbdvDmhv/xM5rvvotm2na3vLSXIXU337Etovv+O8kr1iwMe+RCzzJohnNAhmNkDGpH+2iy0p09jSEuzLGt05TKYzdV6jBauXUfZyZPUefU/KNzvbERTkiQ0mzbh1KkTZq0WZYWFzK1GKc1miS4f7uP38iG2C8ZvEuIn1cGog/IiWNLHQrOTzFDsMgJn5QXkZalgKIV6rYV6q2QWFhNJv9v2M+034dH3RWdbBVtHb0Gvu7pNTM+4ZiMykj7zNcs1UxnBPy4ja96Hlu8mePlPJI21jk57TZ2K7/SXbno+/s0w5uRQduo06iaNUQUFUX75Mrr4BBzbtMHOx5uijZtwatf2jqx17if0KSlc692nxuWVa64N2dnEdbVezw1Pn7opjf9PxbGvhUDPdTQf+eerIEsSnF4qspAX18G+9+GBiTDwY2ubPe/AoY9g0s5bWx191w+SD9+8TcfnhQhTDSi/epWMWa/jNXUqrn1rvg7uBobMTEoO/IapoICcjz8mZNVKBsRMJ0ebg7+zP2kl1nt6cfQ77J3eh3AfETyGzBTZ85j3+9H8s0ko3U9Z2nao24nPen5KgiaBYZuETdiwiGHM7jj7nu7/H0GzpdYi1bLEJzFpQ6q0mdG3IV/sv0ZEHWfWP12NuvBd4Pp5G9T9LPuyrOJ0B0cetPE6BfG8iy2MZdimYXzQ+QO6BnQlozSDAOcALuReoMRQQhf/LhzLOIaTFE49Vy9U9qUka5IpN5bz8emPuZJ/BblMztjGY3nA9wHa1m2Li+qPsR3e2XyJ/Vdz6Fzfmw7hgq0jl8lIzi/l8Y6h1XqZms0SxToja06lsmiv0Lwo0lqtft4b3JS6rmp6NvZFJpORWVTO6pMpLNwdY9OPh6OSgjKxnovajuLyqlnMRn4uvDe4KY4qBZH1BGPIZJYoN5hQKuQ2+1dUZsDNUWlp88zy05bayet9PdktnO0XM4jwdSEmq5i0Qi3lBhPXckq5EV0ivGlSz5W+kX5EZxRzNqWA5x6MINDTeh8urci83o+A817g+98TeGfzZaKCPVg1tT12iqrfZ1GZgRbv7qpmbSsa+bkQ4OHInitWdwiVQo7eJAYGQrwcCfJy4qlu4bQP86wtMbr/qA0+/24wl5ZiyMgg98uv0GzZQm5gGONaP1XxVcr4eWp72oXZFtF/vCeGj/fE8v3ENnRSa7nW9yEAPMaPw33Gq0S9v4e6bmp2T68a/Kw6nszMdbb+eFue60xTl1Lydr+BY/NRJK19n0bl56z76BbEwOxpFOHEqK4tebZfK5v1U/LLeGP2UmbuEoFvnTdex+iZQ7ZbBHZ7ziOt/JFz3uGYZApa59je8KM9Atkw5X0e7xTCprPpHE/IJ61Qy6qp7Wkf5kXmu+9RsGJFleOof2A/dl5eyOzETbbk4EFSpggqk0Pr1gT/9CMyedUb2x1DkkSmIeWoeDkc/AXm+r25enIPsr2zmWqaSXKJnET1GOs6ge3EC+StbninfoDN1YxKD/lKUO/kCmvQKEmw7BGkwiSkHm8ib15J5VOSID8e/de9UOmso7qlLSfjNOD9auvjzOXl6K5eRRefQNacOZhLSlA3b44uLg6prAxVcDDhO3dwpZFtLY7Piy/g/eSTVfr7t0OSJKIbiwyHMjAQj9Gjyf7wQ8ty95EjKfxZ1H6Fbd9G4c+/4P3M05iKiv40r9zM9+dQ8PPPYDBUWeY2eHCVrH/KtCct1PTgH5fh2KZNlfX+EtAWwPwIwQAwVLzETfsN6ra4+Xo3Qfnly8hUKuzrV6+OektcWg+rH7dOB3UQNZuVYdQJpVuXOrfuL+kwfF9hD/LiRWHrlHhQBJzGckAmas5ruAfpU9O41stax+4zfTrmkhI8x48TzBm9nrRXZqCsWxefF1+wsXW6HSRNeJyyY6I2TN2sGSG//Eyb5W3QmayWIcbScMx6L1YOXUDrICsdc+v5DOzt5PRqUofoTA1D1o/BzjEJe4UDJ8Yes7xIPrn7SRyVjnzU/aM72rf7jevBZy/PGew5WQeVnZy80qo2M8383fhq3APUc7+zc1sTLqdr6L/oII3rurJ4XCgfn5nH/tT9ADzR9AmmtZjGjoQdlrpTO7kdRrORTYM3EeoWiiRJnE4uoHFdVwrKDLy98RLJ+aXEZIkavU9GteSRlsIfWm/Ss+TiEnoG9bwtei+AVm/i8LVc5u0QlHgvJ3uKtAY+HN6cpv5ufL4/jg93XK1x/V6NfenVuA4nkwp4sls4pTojuy5nsuxwkoXuKpdBiJcT8bml9Gvqx4ioQHo08q22v52XMtl6PoNN59JpEeiOzmDi+Z4RNKjjwvtbLxOdUcwjLesxsVMoRVoDJrNE47oufyiQORyXi8EskVmk5bV1F6wMsgq4OypxUtkhk8HT3euTXVxOqLcTvZvUqZFy+ndCqc7IwdgcejTyxd6u5ox4eqGWhbtieDQqgKS8UoI8nfjP2nOk5NsKIzXzd2PV1PY4KBXI5TI2nk2zyXaDYPDNHvT/J1z5L0Vt8Pl3gbGCRlq0bh3Z8xdY5n8wQs7ZcDkPhw7jpZYz8a3GNLr03Aae+DmWei16czYuk89+FNkonxmv8FhxBNGZxfiRx/cPKWncvUKAxqDleGIBI5acsemrV+M6fDshCs36aQwsOIgJ+DEji1CD7ahfWcMhOF4V4hXlMhnqbq8JK4N9H0DiIT5wfI363y+EABkDg4/jgHjJOHMxFPVFHTciy8GDSX1eo76vM7tetipg/ngkkTc3Crrpd49H8UDscdJn/Aenbl0pPfBblX4Unp6om0YiU6oo2bsXr8lPoI6MxLVfvyptbwtJh4VJequx0O5JWDtZWCIAyORovSKJSn2RS2pRuzNN/xI7zVFccxiPwSxHLTNA1CR4+H832UgFzCaRBQl/EEpzhB9iSBcYtwEUVR80Gq2O0d8cF1nn6d1xUdvx7pbLnE4uwGiSiM4opA4F/Ff5LSfMDVmqGMLBV3vZFP7XhIx33rHUCPtMn47XpInI7Oww5uUhUygoPXqMtBeFDYA6MpLAr7/CzusP2D78w1AeE0PCoEdu3bAahG7aeMua7HsNc2kpsV274dzzQRTOzhSsWAlKJfXm/hd1o0aoQkOrDN5IBgPxjwy21HTX/eAD3IcOqa77vw5ST8K3PWHML9Cgr+2y86vhwDxQqmHUSnCvoJWf/wVidkDLseK3KZNxpUkkmM2EbduKfVjYne/H1lfgxDfW6du9R9QEkwHeqxiYugul5+TJU6oVeQMxsFeybz+Zs2cDYFevLkFffYXC2xu5vX2NGe/iX/eRs2gRqpAQindYA2uvKZM5OjiC1w+9btO+JHYmktGdc2/1sWSIqkNSfj452lweqBdh8+J//T3mr5bVuB58PhHyBU927ECJzkjU+8LKI3HuAD7dG0tWcTlvDGhyz/0Om8/eiaYiY9c70oWjZqu68fU6zMpo5duKZf2WAbD0cCJvb7pBCOsGzOjbkLMphZxJLmTtUx0I9rL1vZYkqVo7D53RxIgvj3Cugh4Z6OlgE0g0rutqUfQ/93YfNFoDp5MLyCvR4+qg5ERCPj+frCoiJpdBqLcTwV5O1Pd15rV+jf5y10NNuJKhYcWxZCZ2CkECDsbkMKptUK0HZg1IL9Sy9XwGapWCJnVd8HKyJ9jL0eb7NprMjP/uOP2b1cXNQclzK8X77q8vdyPM58+n5f+DURt8/l0Q92BPZCoV3k89aVGpPdpQxv+GyJEqfkwXJlywmDLHFcQxZtsYBgT04O19XwIQUi4ygts3CA+9uGFDedDuGy5KobSTVwhuPHMCzq1Ef/RrygwST5te5v3BzUh2acnj359gy3Od8XfR8OyqXpy3F0FKqN7Au7l5vBPUgEmtn6Pvhe2oLgua5kZnJ97w8UImSayWBeCZfAwfk63hM8BHhuF0jAyl/sYvyDlnFYFwXvgJB5dvxq9DFO2njUWGDAeV9WabU6xj8Ge/k1aoxUml4PRbvVHJZSBJREfWrHYH4Prww/gvmH/H34UFsXtg+TDrtFugUI0EiBwCwZ1g2yvsNbWip8IaxJsbPoz86haMkhw7mZmEyGdJbvEi3Rr4YDZL7LmSxVe/xdOtgQ9tQjwtdKIqKEoD5zqWwDMpr5THlhwjJV/L5M6hllqJmvBkt3BGtw3EzUHJ3O3RrDoh9j3I05GPR7XEx9meAA+Hah/O2vPnSRwxEoDQdWtRV/IhvY6cRYvI/VzUtTp17kzQt99UafNPhTE3F4WXV40vNqWHD5M86Qn83nuXzDdFZsGpSxf8P1qILjqapHHCVsNn+nRyPrLN1NR56008x4yp0uf9RPzgIeiiowlesQKH5s0o2rAB10GDkKtuPlBROcMLUOe1mRgyMlF4euI5YbyN6JWxoAD9tWs4RkXdt+O4JQoS4ZOKjOekXRBUUeMmSfBOJSpi81Ew9CthUbL0YeG3CRD+IOVx8ST8bM1chW3ZfOsMaMpxIbzjXVHb+Vk7cT/xayaotQ/Ng/Y1MwiMBQVIOh1Kv5sIz5xaKu4XDR+6+b7cAH1iItce6of388/hNugRSwZU5uCApLUGBPYREbj07Uvu4sU269ebPx9jXi6G1DR8X3kZmb09klZL3IM9MRUWWtp5jB9HwbIfCVz+Ix0uThTbzu+InfNV5HIzbzT/iZ2Xsvju8b9oBv0u0XJpa0wYmNFwNePbC7G26EwNbg5K6rrdmyxnTbiR2dQx3IvPxjXkt9TfSNIkEZ0fTbhDdxZvN/HagGCGNW/Jjos59I30o+fCAzZ01U9Ht+JkYj6Pdwpl75Us3t9qq7fw4bDmjGhj1QE4m1LI5KUn0ZQbGNban7HtgjmWkI/ZLLH1QgZnUwoJ9XZi+AMBPN09nLjsEr45GM+W8xkoZDK6NvRhXPtg2odV/3zcej6Duu5qTGaJF1edZUqXUB5p6X9bg6u1+Hcip1hHuw/2YJbg9Ju98azmWtl2IQO5DHo38atWKKkWt4Xa4PPvAF1CAskTHsdz4kRk4fXJmjqFTHd4/ik7RoRNw8lRz/cXv6dbQDcOpB5ALpNjlqwB3qGkFNzMEmHlP2FGzqrtb+OmKyW4Zy6OPlXpPQB7TK1oIY/HR1aECYgb/jX1Igay/cAs3ssQtZr9fKLQ2qnYn1G1luiD7FwGylyY3KQ9x3KsgVcdo5E9Kek2bU8ETMT84Ju0C/PCcG4vac9Mw6e1ATtFCfbB9aD3exA5WDTOvgJOvlXM03dfzmJKharui70ieLFXA8xlZZT8/jsuPXogs7Oj9NhxkidMwKVPH1z69sExKgplndugrFUHbSF80VH4X7Z7Co5ViAeNWAZ+zcEjBF1OHPafixdpySMMWbNh8Js12P25/mv4Xt3MK4ZnyEPUg9RzU5Neoeh2HUdf68nOS5msOpHC+4Ob4utib1O3AcL6ZvBnv1sU5a5jYqcQXOztWPSrsCDo3tCHKV3CSCvUVvGhu07PvhEDmtXl09GtbPy5AEqPH8eUn4/rQw8hSRL5pXq8nO1JyS/Dyd4OD5WMos1bKFixAmN2NuG7d6HZsgW3Rx6h/MoV7Bs0sFXc/YfgemDuMX4cvtOnU7R5M8aMTJwffBBzsQaH1q3RbNlCxutvELZ5E7q4ODTbd+C/cAEypcjoFG3disrfH4eWLSn5/Xdkdkrsw0KJHzgI527dqDdvrs02y86cQeHqahEKM2k0lJ04gbpxY3IWfYpTxw6W34DXlCmoAvxveRym4mJSn3+esiNWUZdGVy7fcabgRir2dSj9/Qnfs9vSX8ozz1Kydy/By3/C8YEHADDr9bcMcO8pjHoh8JV2SgR+0w6IeuvY3bD2CVEPGrsb/JrCyOXwSXNB2w1/ECnjEpRkkbTPC22OPQp7EyadGCjzfuYZfJ57loKff0GmUuE+RNzPTIWFZM//EOfsb3Hx11mzkh8EQOtx0OUVEXx2edmqiF0NYjp0xFRQcF8E1vJ++IHsufOov3cPSn9/JKMRmZ0dktlM/g9LKVi+HHWzZvi98Tp23t5odu8m7bnnb6tvx7ZtsfOrg/e0aajCwjCXlnGw4ATP/focAMVX5gAK9s/oSojXn6SGfJ9xKuM8nxzZwLeD3qi2RvF+QpIkei48QHyutWYwca5V4G7FsWRmrRfBqb+7A0azmSyNlZm0ZEIUXs72rDudyuyBkZZnhCRJXEzTEJNVjKeTilnrL+DlrKJrhA+acgMuaiW7L2cRl11CnyZ12HXZWot3HfOHN+fRarxSi8oMyOTgWuvvWIv7gJlrz1sG4ge3rMf8R1twKC6XjMJyIuu58shnQktDqZCx+6VuhHg73aw7G6QVaqnnpv7bZNvvI2qDzz8L+StWULDsRwI+/xz7sNCbtk175RU0W7byxWOz2VFkzxPxX7G3UyqfjN9AY+9wUjQpDNowCKNUvWz36KJini8oZEj5PCbb76XHucPkXXEheGAuajcFuQMXojn4CfVzRf3EB4bRJDSczKLAA9gdeJfWoUEAuMvtKTSLB0+HcgMLxx/mfP4Vntxz85q+Kc2msPbSMvIr1j02YB0OcXuRyRXQZnL1dUYGrTCf3/VG9Z0+f1YoZFbCd4cSeHeLMDqu/ACtDMlgsLzg/yEsaAAlWdD3A2g5BuaFiKDzyYOWJp//Gs3Tv1VkTibtBN8mcGE1qJygTiQTTi3mdFoyxfHPVun+09GtWH4siaPx+VWWudjbsfHZToR6O/Hd74msP5NKdEYxRrPEJ6NaUqQ1kJxXxgu9IixqcuUGE/Z28pve9ExmiZT8MracT+dEYgEHYnIsyz4c3pxHHwio6MtsyT6bzBIX04p4Z/MlTicX2vQ3s18jnuwWTu6XX1psYQC8pkwh75tvUDdrRvDyn/5/g4vbRNnp0+Qt+Q5VSDC+L7yA7DYyfOXnzqEMCiLr/ffRbNteY1v7hg2Rq9XoExOpv+/XOxLiSXn2WUr27MV1wAA8HhuLY6tWGDIziesuqOjXayvTX5tF0fr11fbh1LULQV/fRB21AvkrVpD1rhCgkTs5EbxiBeqG1dN9D6cfZv6J+TT2bMwHXWxVRg1ZWUgGA2VHj5Lxxps2y9wffRTXhx+mYOVKC/XStX8/6rz5JokjR2FITibwm2+QOztRfukyDi1aYOfthbJu3Vvu/x/CztfhiG0GjzrN4PEtQszr0nrwqi9qJ4HSFgtIfu0jFA4KTFoT3k01uIeXkbDdB5NegdzFBd8Zr5D51tviuEeOxKl9O9Jemm7pvvGodHjuNJTlwZLe0Gs2dL49wa7rAb7f7Nl4jBp524eZv2wZRRs34TZ4MJ7jhFiYISub0iOHUTdqhD4pmdwvv0QqLyd8+7bb7tdUUkrW++/j9sggDJlZOEY9QOGateR99ZVNu4DPFuPSs6fNvFXRq5hzbA5lyRMJc3qAmf0a0bPxXQ4S1uK2oCk38J/V59lxKZNDr/Zg07l02od58fr6ixZ6640Y3yGYtwdG3lb2Z/2ZVKb/cq6KxUebEA9+mdaBZ1acZtuFTGb2a8TB2Bym927IA8Ee1XdWi1rcR0iSxOf7rzF/uahdzAAAIABJREFUZ/X1xCqFnAcb+bLjUia+LvZkF+sY0y6INwc0oVCrZ/nRZEa2CcTX1d5SpzpvRzRf7Bc2gw9F+vHho83/7YMntcHnnwGTRkNMW6tkue9//oPXJEEzkiQJXUwsMrkM+4gIJLOZi+07ccA1jAVRgmrnELiE+nVlbB661tJHfGE8P1z6gaERQzmYdpBwt3DM51bxc/ZRzqrtCdfrWZzjSIA+HkmCsmIVTq56RjTtwJVSoSS4uOUyHl+ZSrswb5ZOasv59N/4+PfZnNdbA6D6RjNfe3fBJ6IfNHkEnUnHnKNzqO9en/GR44ktiCWvPI8pu6YAIEPGsbHHKNIW8P2J+axI2WPpa2G3hfQJuYVqYkkOLLBS1g45qFnk4c6w0AEQ2I42fm0Ic7fWVC3YeZXF++J4e2ATujbwsSgi3hMcXIgh8wrK/nNhvsgwRY/4DZ+gRjikH8UxsLnFs27P5SyeXXmamX5neLxnC2hkDYYPpx9GLpMzff90+gT3YXrr11Ep5FzJ0BDu68zhuDz6RtZBJpOx7Egib228hL+7A28PbMKs9RfILbHNVjeu60pOcTlN6rmxbNKdm8LnanPxUldPETWZJQZ+eojLN7yA+LrYM294c9acTGXrhTRARqsgD85UBKDX7XW6NfBhbKg9gU+NqnH7rv374ffuuyicb++7MpWUoj13FmNmFm4DH75lYHg7kEwmkMsxJCWBnR3XelntJhzbtaPOrFloz5yp8cW+9OhRkh+faJn2GDuWkgMHMKSm1rhNv7ffwmP06DvaT11cHJlz5liykcEV4lpJlWi4bo88QtHGjdj5+uI1+QlKDh5C6V8PhYcH+sRESn7dR8MTx2963iSjkaTxE9CePk3IqpVV/HIlSUJn0qG2U6Mz6ei8sjPlJpGx7x7QnY7+Hekd3BtvB2+bda5TcOstWED6K6/UuH234cMoWrO2xuXhu3aiCgqymWcwGyjVl1ZR6rxdrI9dT2ZZJlObTUWRGytqql39oe0U8G4o1KhVTpBxHr7qIlZqNgIiepOx9rJFIEoVHk7Y4leROfnAgbnkr99F1umq3rg3Iqx/NvZuZkx6Cb3GDh5ehLrP6FuOkhsLCojt0NEyHfDF5yjr+aNu2IDy6GgKVq1CdzWGOrNmYefjTdbceeivXUMXa8tyULi7i2skJQWMtgOZXtOm4fvSi7dzGm8KyWxGJpejvXCRvO+WUO+DDzDbK3lm7zP4OvryStQrLD6zmJ+v/oLmyntsea4bTf1vfe5q8cdROctZGRM7hfD974mW6U3PduJqZjHDHwi4owxOlqacgjI9h+PyCPcV9/rGdV3wdVFjNkuYJAllNWqmtajFn4EbKemeTirs5DKm927AqLZBDFp8yGLZAtCgjrNFbOs6fpvRA5Mk0WPBfss8mUxk7ad2DeOZHjWXY8RkFWNvJ69SJ/0PQW3w+f8NyWwm9/MvyF28GKeuXSj97SDKgADq79lN1n//S/7SZZa2hc4eqGe9jXrWi3zcZjRj33yKUzlH+S5uFgPDBtpmGPbPg8OfQv8PhfLpFx1Bm0+6nYK+gYJityY1A2fJTD2jCRlw0MGJp/1s6asvNZ9D3/BOLDw9h91Juy3zB6kD2FSeykedPqB3/RqMyiuhsLyQtbFrGd5gOG724uWhRF/CjsQdvHPkHQDc7N2Y1HQS9ZzrkV6STlZpFn5Ofqjt1FzNv0qJoQStUcuQ+kNwlNlxJW47H6dUHX1f1GMRPYJE5mfvlSyeWGq9lr4Y25qnlp/m7YFNmNjp5hnmG7HudCrvbrlMz/K9LFR9WWX5SNN7HDOIINRJpeDXV7rjqlYyZ9tlfjqaTJO6rnz7eGtM8nwCnMWD2iyZabHMqqI5p/McBoUPqnEftHoTn/4ay4ioQEK8nZAkiVbv7aawQuK9QR1ndrzQtQol9nagM+nYFr+Ntw6/RfeA7ix6cBEavQadSYcMGZ5qTxRyBRlFWh796jCpBcUg2Y7W2ftuRuV5DCeFN0v6fYybIhStUYMdzvRYeMDS7j9Zh+hxZANOYx6jdMVPANj5+mLMtnq+uQ4YgGbrVuq+/x7uw4dTE1KeepqSffss08ErVuDYulWN7W95Hq5dI37oMNDZCl3FRNWhwUlbOlhlO5HrKPntN1KmTrNMy0OCUC5fTFZ2AgFrjqBSO+Lavz9Z776H19QpFKxYibppU3yef65aC6DbgfbiJRKHD8cxKoqyinun5xOTyF/ynaWN//8+qiKkpdm+nbSXpuM2bCjqyEicOnTAPtT2dyGZzaS9+BLFu4R8fWUq56msU2yN38rqmNVV9mlKsymsiF6BJEmUGcsIdwvn277fotFpLANE2pgY9Kkp6Ns3x11vR8b0Vyg9fBiXhx5CFRRE6ZEjlF8QD3z7iAj83n6LpMfGVXsOgrZtxilMPLxNZhMPrXuIzNJMxjYeS5mhjG4B3XCwc6Clb0scldbscrImmdSSVCK9InFUOmIns+Na4TWGbBxMq2sShqhIvh+wDLW+DJSOQmDoRsTthdQT0F3U3yeNn0DZ8eN4P/8cno89hsK1om7dqEczqztpm4RgnOfQvjh1aEvqrLlIFarB9QdmErdZ1Gp69YygLLEI7TXr78LnpZfwGDUShVvVIEwyGkkaNx7tmTPIXV0xa6rPUslUKiR99SUWXpOfoOTAb5Zg1D4iAtf/a+++w6OssgeOf+9k0ntvpNF77yBIERQLYEddFVSs6IrdddX9rSv2gmWxF1TsCihVFkGQXiKIJCQklEBI733m/v54J5MMCVLGEELO53l4nmRa7hzedt577r0XX0zZ+nW4d+iIZ5/e+J533ilvq8di1VYqairILMtk4veOk29VF/TFo/Batj/+1y7pIo7tUEE5Q5/5H2BU17x0VW+OFFUwtks42/bnc/unW+kQ5tPorPhCnI1qLFZe+18K47tF0DXKzz6nChgzEV/z7gbGdgkj+UgJ+/OMdVWPvllTq3ZFhs3peVw+x5gjIP2ZC5m7Lp0+sYGkZpfwwrIkLuwRxaIdh+2ft+PJcfxxuJi56/fx5MVdyS2tomN4ix+CIMnn6aK1RldWcvifj1O0cCEA8V9/Tf4331A4bx6B10wh/7N5WFGYqIt37e9eC5bgF+vHiC9GAPD8yOc5P/582PQeePjDd7eCtca4U19dZoxDAjj3UR4zFzM/db79M2/27MqI1P9xfZRxwfPwwIfRWvPspmfxcfXB392fI2VHuLrT1fi5+zGp3ST83f1ZkLqAKzpe4fQi0O/ueJfiqmLe3/n+8V98lDCvMF7y7opp++c8GxxIooc7fbUbHyVcDSMfQGvN80uTeNNW4lDfYxd2IczPg7LKGnrFBLD090zGdTUOKvVZrZp31+zl6UW76aVSmO/+eIPPWmnpxU3VD+Dt4UbXSD8278unS6Qv6TlllFTWcH63CF6d0ps5v73OuzveZWK7iTw1/CkOlRxi/Dd1s2gumryIGL+G41r+jMWqmbsunRqr5qKeUUT4N3JxfAxl1WV8kfQF3+75lvSidIfnzMrcaOn2oMhB3NB1KnesuI0XRrxEz+CB/Hv12yzeEIZ3wmyUS8OL2lDPULoG9uPWbg9w43uJ5JVVcWH3CJZv28echFJey/YmpG0sT/b1pehvU9AVFdTWZLlGR9N+xU8NPhMg7ZN3qHjKcQKeioHd6P3RVyilHE4Ojdl6ZCsf/P4BqVtX8s/PLLjExeCVdgSXCsfv8NlIE98PUQSWwFuvO874mN09il9u7k+HhH70COlBwdU3EXDA2N+ufKThrMOhnqHMnzTf6TXtjuaQhCtF58TtVKalceTpWQTfNA2fESMavOfoqguAyGdmETBpkv33gu+/5/DDj9h/z1o+h6T8JLZmbWVtxlFrx9rc0uMW7ux9Jy4mF7TWfJ/yvX2JhloXxF/A4vS6cuQZfWYwpfMUaoqL8fMNpkRXsCl1FZG/HSauTXdy2gayrWgXnScZpbpPXOtCRL7GrQZuWmZlRS/FwvODuHh5IV0f/Bf3JD7RaNvcTG5YseJqciXMK4x9Rfsa/w6LLZy33dgGk2NcKOwSReA9M3BRLiTlJ5FemE6vsF4MihhEt5Bu5Oz9A8+IKDzcvUkZOJji0f1InjaSSztcyuqDqxkVOwpXkys1v37KkScfJbhrCR4Bxv6lH82kat9BXEt3YPp+Krlu0yjcvI/KXcces+k7fjzRL7+EMpmo3LOHqv37qUxOJvvV2YQ99BCB10yhau9e0iZfan9PwJVX4t6+Pd7Dh7Pvhutx8fMn+Oab8R11LqXr1+MzapR93HV1RgYVSUn4jBrVYB86VHKId3e8S5BHECPajKBHSI8GM8nOT51PUWURw9sMJ9I7Ek/zn0+W8+HOD3lxy4v23y/rcBnf7PmGANWFA7uv4L2/jZBy29NsxrxthPu6M3NcxwZLdfxxuIggbzfCG5lRX4jWyGrVKAVb9+fzc1I2t45sh4+7Ga01S3Zm8vWWg6zYncWUgTHMurSn/X2zFv/BW6v2cuvItry1ypgN3t/T1WECrz8zZWAs/5nU3aHTQWvN7BUpbEjLZfaUPoT4nNHzaUjyeboceeZZ8j780OGxOfe+yR9bd/PqKmO9yyIvf64Z+yg+1WW8Z96F98K63oUuu/9gyg9T2Jm7Ez83P9ZOWQvJy+CzK+o+sPNFxh35GtsMhF0uhivnUq1r6Du3r8PfDnX1I7u6iBl9ZjC9p7He5cLUhTy65lEivCN4ceSL9AztSVNamr6Ulza/RJW1itExo3lw4INkFGfwVfJXXNT2IrZnbyfGN4bfc38npyyHHqE9GNFmBEEeQZCdBG8M4h1/X2YHBfBmZhbnzEy3r1F5uLCcIbOMu7gX94oi8UCB/U5Sfa4uiicu7sZ1g+Psjz2/dDdzViZzo8tS/ulq9NLlal/+z/sxnrl+NLNW56HdfBjXLZzh7UNQSvH26lS+3HyQSH8PYoK8+PvYDoT5ejDz55n2HmRPsyfnx5/Pdynf8eVFX+Ll6kWsbywf/f4R5ZZybu5xM66mUx8HUG2tpqSqhEAPo/RXa82yfcvYW7iX23reRnZ5Ntcvvt6+YPugiEGc0+Yczo05l6lLppJdnm1vp4+rj/33+hQKjePxYO4Fc9mUuYnZ22bbHxsaNZRfDxkTUY2KnsCCFYNBu6LMRWiLN2gTYCLY240Hz+/AiGhPTHM/Iu+DD3Dt3Jn23zuOV6y2VLM57Rd8LrkTsxUemurCJeutDPtDsysGnrzOdqGkNTOXujEmciRR/3gMc3AwFquF93e+z8bMjaw/bJSrvvtKDX7lsCcSOhw23rozTrH2ik4Ed+tL3/C+jIsfx7pD6/h67mMku+VR6QpPf2ghoAwqzfDKJBMPfW1M7FVphnfHm/CZZFQF5Ffkk1ueS1K+MW4kwjuC+/rfx0OrH2J83Hhm9p9JeU05sb6xp3wzp3z7dtKvnkLgddcR9sD9Jzx5U+2yGUFTp1K0ZAk1hw8TfMst+E+8BJOfH3kffEjeBx+wZvZ1fJc4jwNhdeeJie0m2pP8v3X9G2mFaUT5RDU4VmituX/V/Szb9+eLf9fnafak3Hbscndxt6/x2DvVisUEboMHsL9oP8OihzF8zgYiEjPICFEkHLJQ4Gti+l0mrup0FSGeIcT7xaPR5JTncLj0MAtTFxLqFYqvqy99w/vSPaQ76w+t59s931JlrQKt+fhtTzzy6sqmyt3ghpkuoBSu1Zqx2zU74xQHwhQzFsE5iTVk+Ruvi8uGt8838VMfk8M+MrHdRB7udSc+Pz8LWz6o+7KT3zKOz88mgLbCAyngGUD5jh2Ubd5C0PV/A63J+3iuw/qvQdOmYfL2Iue1uvGoHj17kvDlFw6xLPzhR6xlpQReeeWfxtyqrSzft5wI7wh6hTa+rml5TTmT50+2HzcAfF19ubCtMZRgYORAFIp7f244PjXaJ5o4vzhCPEMI9Qwl0COQtMI0iqqKHCpr+of3593z3uNAQT7jXt7AlAGx/Gvin89WLoQQLdGvqTlc886GBo/PGN2e4ooa/D1dufmcBK5/f6N9KNOYzmH8kpJDVY1xzdEtyo+nJnUnOsCTx77f6TBp157/XHCml7BL8nk6VOzeTdqkuvXt3MaNZ2dmKfckTASl6J2VzKxf3ybDO4Ty97/gwh6RmEyK6owMUsaMxXv4cNbdP5anNjwFwPxJ82nr3xYWPQgb603gcF+yseB4yk8Q2Ru868ZbLU1fyv2rHMdYPTzwYa7tcq39d4vVwuL0xQyLGmZPYM5oVisZ2b9z/hJjvNtDCZcSFjuMwVGD+fe6fxNm7o0PCeyqmMdl7W5kxfI0/p1xE8sjb2V6+kgGJwSzN6cEH3cz86YP5tI3f+VgfjltVDYLPB/kZy8zR8wuTLZ6Eni30SPxZwsdN+aGxTeQU57D/uL99scC3QNZddUq+0X8o2se5Ye9P9ifv6/ffXQK6sTgyMH215TXlLM0fSk/7P2BpPwk3jrvLboFd6PSUklaYRoeLh48tvYxErMTGRw5mEs7XMqqg6v4ce+P9s9VKDzMHvxr6L+I9YulW7Bj+Wh2WTYB7gG4uhgJcGZpJoEegfxz7T9ZnLaYKO8oKi2V5FbkAnBN52uI949nSmdj3GJRVRE55Tl4mb2I8I5w6NnwVpGU6Ww0jj2rVbnDcfFJxuRSQnVhH25ek864lEx6bt+KMpnIKc/hk9l303t+IlsTNBds0cy8YAK7vfvgEfU1Ny8vZ8If+/m/KSbCCuC2xXWzPC/ro3hvnAltuzvo7uLOiDYj+EfP+8gaaiwX4bJuPsUXXIVXQYVDeWlljYWVu7NZ9nsmIzoFYDJpSqoLGdjWh+JX38Tjc8cJhWJ/mI93e2MynmqLlSU7M6motnBhzwjuXnk7GzIbnmhqXdvlWpanL8fVxZVgz2BePvdlwrwaX+jcGSn5KaQUpNDfvzuFeZmkmHOJrwnAetGNDV5bHB/KTVOM3tza2bP7hvXlw/M/PGbPckW1haKKatxcTPh5uGIyKTJLM8mryMOqrXQJ6sKegj0k5SXhbnbngVUPMDZ2LF2Cu5BTnsOO7B1E+0azM2cnAyMG0imoEwHuAeSW5xLmHWZUethUHzlC2uRLseTVjUe/fqYL31+zlCivSHLmzCHwqqtOaG1Zq9VK9rPPkffRR4TOnEnQdddS8NVXHJn1DC5Tr0aFBVPz7Bv2128aE82AFRkNPmfhfYOo6tGe7Vnbya/IJ94/nk2Zm+ge0p3HhzxOZ9cAKDgAP9wLOUlgsfW2B7eHGVsabZu2WqnYsQOPLl1InXChwxhi5eFB2L1/J+DyyzF5n/y4oMzSTM77um5s86UdLuWaztewNWsrT28whnT4ufkR6hlKamEqN3a7kUGRg7j9p9sb/bw2Pm14YMADbMvaRlZZFovSFuHt6k2IZwjVlmqyyrIaVFa8NfZd9uUV8ujn+YR4BZNdXImnqwsLZwyjfViLLy0TQohG5ZRU2tfzXXHfSL7bmsFdo9s7rNtabbGSWViBi0kRFWB0rGit7RN0Ha1XG3/+NbE7vWNObd6D00iSz7/Ktv35eLmZ6RTheMKsXc+vvosueRaLyYVrB8UyqG0wD328jm9/fIzFF01n5guOd48tJSVkVuVw/kKjR+Wny38i/OBWo9R2ycPg7mfMwKh147PG1rMsfRn9I/ozfdl0kvKTeH/8+wyIaPlrpr3w67/5aM+Xx33dG4UWzsnLwAKs7Hslb1izKSvzJTW1H5bSDrgG/YKb925uLUvnnTDHUsu3z3ubIVFDTrpt5319Hv3C+zFr+Cz+s+E/fJP8Da+PeZ1h0cPsr8kqy2LMV2MavNfL7MXYuLEkZic2WipYv6eoVqxvrEOie1mHy9hTsIffsn8zYjDmDUa0aViO+WfKqsvYnrWdIVFDUEqRlJdEu4B2mE0NS0yPdqjkEPNT5/Pm9jcBMJvM1Fgbn5UZYPR2K7cttvLu36dz+SWDWfT5a1zzdt1SPZsi2vLFpQ8zfURbViVnU71+HXcsmu3wGVUB3uRRSoRt8t3lM4fRcdzljI8bT/7cuRx5ehYAwbffRtg992ApKsJaUoJrVBRaa6otmts/2cKK3VkcrVcbf544tw2elxtjKduvXoU5NJQjRZX847sd5JdVkVlYYV8up09sAHee2x5Pn0z2FCRRVRJHjWcieZVZLEhdgKfZk7wKxxmNx8WNY1r3aaw9tJap3afianIlq8xoy+683XyZ9CVmk5konyi2HdnGxPYT6RzUGXcXd+L84hzGNwL8cvAXFqct5qf9P1FeU06IZwil1aX2bce/RPPOa47b+/OXmdjU0cTlHS/nwQEPorVu8Ln1zVmVyovLkqi2OJ4rUp+egIIGY5Jrb6j82WceT3VGBoULF1K0dTOVq9fyw4x+PHDnJ5Rt3WafgKnjxg114y9trOXl6MpKXAKME3TRokVkzLwPgA6/rsUcFOQwg/CxBNw0FY/4BLJfnY17QgKxH32IMjnebf5uz3e8tOUlXE2uDIgYQKR3JO3MvkSseY3e2Wm4Aty21li65ThK1qwl/5NPcAkIoHLvXmLff88+SZfFasGiLbi5HH/yrd+yf2NT5iZe2foKAN2Cu1FaXdqgDB+gfUB7MkoyGB8/nn8PM2Y+tmqrfSmv3PJcvt3zLQdLDnJLj1uI94+3vzclP4U4vzgKyqzszCjkYPEhzJ4HmdRpLKU1JXy1NZmXFxVSZVv3OcjbjfyyKp65tAdXDYht0BYhhDibrNmTQ4CX60lPqqa15kBeOe+u2cueIyUMax/MXaM7NFErm4Qkn3+FzMIKnr3pccp8A3lxzgP4uBsX5Ucnnhde8ixeNZWUuBkXXN/cPpR+cYEkHijgXwt/5+ELujAwoeFabs9vep6Pd33MZe0v5clSizGxUK2RD8GoR0+uvaWZLEhdwE3db3J6/OaZIunzK/gqexOJUV3ZXXLA4bkbCotYHhLDoerCRt9rqQyjOn8wHhELHB73NHsS7R1FSmHd+NEgjyD6hvVldOxoYnxjWH94PZd3vNxhVk8wDg7/Tfwv/038LzP7zWRqd2MmVIvV0mjMd+Xu4q3Et7il5y3M2z2P8ppyNmZupLDSsc2XdbiMBP8EXtj8gv2xp4c/TXlNOe0D2tM3vC+rD64mOT+ZoVFD6RpszC56oOgAVdYq2gW0O14o/3IWq4UXNr9Agn8CV3a6kvTCdDYf2Uy8Xzxmk5nMskyGRg1lWdoKPvn2n8z6yMLWdopnrnThqlUWLvu17vjz7vjbef7lGfZkpriimm8ef5VBC96zv+aJe97jwcqdeM95GYCw++8j6IYbwGwm/aqrqfjNSMTz/vUiseedS5ifO++tSeO5JY5Tq985qh1+Hq78uOMwGfnl5JbWjQudoVO5/Y5JVIdG8sDXiQ4lL21DvHn4gs7M336IH3ccbhCPTuG+zJs+mB0ZhZhN0L2NN37uxl3NOb/NsSfqAN2DuxPuHc7KAysd1u71cfWhpLqkwWcD3NH7DtoHtOetxLcorym334yI8Y3hvv738drW10gvSmda92n4ufnxedLnPDD7EJ7VioOjOmH19SZrXB/u7nvstRrLqmr4blsG5VUW9uWWMXf9PtqGejOiQyiR/h48vzSJGmvd/1v/uEDuGduB4e1DWPFHFqnZJVw1IIYArxObqdhq1RRVVHMgr5yckkpGdAy1L/FgKSkhuX/jN9GCpk4l/KEH7b9rq5X0y6+gYtcuY8kbHx/Ktxi9jtGvzcbvvLqewNING0FbcY2OpvrQYVyjo6lKSyPruWdxa9uOyH//X4PEtjFrMtY02lvoZnLjjh43cVPvOxwe11pTo2vIKM5Ao0nwb3yitBprDfkV+XiaPRkyz7gx1jesL8+NeA5XF1dcTa74uvmSVpjGrtxdVFmqWJS2yF56DvB/Q/+PyR0m28fpVloqaePbhmFRxs2xk5nN9Jc92azZk8OB/DKqajThfu5sSMsjJavhdnrriLbM27ifmCAvukb6cd3gOHrFBFBtsZ7p5WJCCCGcI8mns7TW3H7XbO5ZMQcLiosmPccPM86hk6mMzKf+Q8mKFayf+Szv/pZHhk8oj1/UlX5xgSzaeZiHz+/c4OT+ya5P2FOwhyjvKNr4tsHD7MG9K++lR2gP3q/yw337Z44NuGszhLSoOx5NY+M7sOh+rMDvbm50qqriKz8fYqprGFFeQZ7JxJNRsax0NS7gu1dWMq2giN1ubrwdWHfX6dzSMg4ERPLwqBcYHDkYgOT8ZC5bcNmf/vkhkUN4ZdQrFFQWsCB1Ad+nfE9GSQadgzrzwfgP8HE7tSVfDhQd4Il1T3BP33uI9Y21l0PvLdxLnG/cWXPzoFZlWTF7+xrLxSy94jL6/281PhYrxQGhBKYnUTp/BYM6NVzjsSzzCO8t/o11K7fwa1QPlLbyYmwp3d57HmuZMdbXNTqa6owM0uO78XCXKyh0b/h/4u/pSoSfB9NHtOXSvtEO+2dqdgm5JVU8Pn8nuzOLHd7n5ebCxT2j+M/k7pjrXTzvOFjIxa+vwdVF4e/pRt/YgAYLqo/rGs7sKX3wcHXBYrXw2e7PKK0upcpSxTs73gGgT1gfzCYzQR5BzOgzg1jfWMprynF1ceWh1Q+xfN9yxsSOYcX+FXVtMnsxNGooLiYXHuj/AOHexuQtWmtqrDX28mrAPvPqn62Buzo5m2+3HmRfXpl9HEqtjuE+fHfHMLxtN96yiioY+PSKxj7GztfdzPYnxtmTyBqLlfTcMuKCvXB1MWG1anYdLiK/rIrH5/9OWk6p/b1R/h58d+cw++Qn2a+9Tv68eQ5luB49elCxYwfmsDDa/bQc5eJCwTff2NfarC/6lVfwHjeOjWl59IsLxM3cMAGqrLGccNn94cJyKqutRAZ44G524VDJIQ6XHmZ/0X783P1YkraE/cX72ZW7i85BnVEoCisLGRQcX/pfAAAcAElEQVQ5iMOlh9l8ZLO9QuCVUa8wOma0w7ZYVFXEsHnDjvXnAXA1ueLu4u5wk8LV5MrgyMFM6z6NWL9Yp8q7iyqqqai2EOTlxvYDBVzx1roG6ziG+LgzbXg8/WIDKa6o4Y2fUxy2nY+mDWRkx9BTboMQQogWR5JPZ2itWXfvPwhcUjc5iinIyu4LL6Dj3KX2xy6Y9AIJId7cM6YDk/pEO3yGdfvnUJ6PacjtbDmyhRuX3Njg78T4xvD1qDfxetU2IcQ1XxqTVBzcBKP/edxy21ZBa3i5OxTZxkTd+CMs+yd4BkDXiaBc0G3P5dfS/QyIGIBbeQFsm0vmz//hnvAQPLTm0dx8OvW7Fc59BI5KTEqqSrBixc/Nj6+Sv2LLkS1E+0QT5BHEgtQF7MrdBRgTcRRXF9M/vD+TO0xmQsKEEypPFXVy3//AYZKVkLvuInj6LRQUlRMUcvzylLKqGqa8s4HEAwXcvvcnLvltif25Cncv/j7sdvb5GQnsvy7pxpxVqUT6ezCmSzg3n5Nw3ASjtLKGQU+vwKTgkt5R+Hm4cv+4Tie83M3K3Vm8tyaN1OwS+sQGNBi78cTFXRnVKQwNHKzYitlktt8IqbboBolRjbWG0upS/N39Kasu44PfP2DbkW1c3+36ky6xPpZpH27if7uzCPV1J7+0yt6r+cylPdiXV8Z1g+OIDnCc3TSnpJJvtx4kNasUpSCruJL/2UqZe7bx57eDhbiZTcQFeeHtbuZQQTlZxcYkQ3NvGsiLy5LZfqAuURmYEER8sBdebmY+/DWdcV3DeePavg49ZTXZ2VQdOEhNbg7moCD2XXsdAB5du1Kxy9hHzVGRtF+2zFjzdNUqtMVK8E3TeOi7nXy52Th+9IsLpE9MANNHtGX7gQKmzzV6R/09XekU4ctHUwfi6Va3nZRW1vD6yhTMJsWWffn8mmqMi/ZxNzP3poH0iW04hj63PJd7f76XbVl1ZeVBHkblS4R3BGaT2V4u72X2IswrjMeHPE60TzQTv59oX1d1TOwYrux4JZ2DO7PlyBbWZqylylJFkEcQazLW0Dm4M71CexHuFU6/8H72pa9Ohtaauev38c4ve8kurqSi2trgNWG+7nx921DyyqrYvj+f3NIqpgyMtY9VqlVVY+X7bRkcLqzgrtHt7TcfhBBCtAqSfDqj7EgW+0b++ZpXySHx3DP8LtY8NIo2gV7kV+Tz2e7PSMnfQ2bhPjLykuhcVcWAAXcze+c7JPgn8PCAhymsKmT5vuUs37ecG7rewP0HUyBxHvztO2g3+jR9wxamuhz2LIe8VBj29xNLynctgB/vg/CuMOZxiO53Sn/6y6QvOVB8gE5BnUjwT6BrUNeTKlkTjsoTE8Fsxj0+/pQmU1mbksO17xqT/ESVZFNudiffwyiRHNoumJLKGl64otcpr5eVX1qFr4fZoZfzVP2amsNj3+0kp6SSogrH8bAD44O4emAMWcWVLN5xmN2ZxVw1IIbrh8QT5O1GkLdRtrpydxbb9uczrltEg/EjWUUVeLi5sGVfPtnFlYzrGo6nmwt5pVVE+HkccztNPlLMY9/vJPFAAZU1VoK83Vjz0Cg8XV1YvzePgQlBJ504ZBSUk11cSUKIN19vOUhaTgl/HC7m90OFDRIaVxfFRT2jKKms4aKekUzsXXfj7o2VKTy/1CiT7hblx3OX96RbVOPrYB566GGKfjQm3vKbcAEhd92Fe9u2Dq/76Nd0nljwO24uJvsYxD/j4WrC2zbG/9aR7XhjZQob0+p6XYO83egQ5kPiwQKsVnh0QmduHJZAcUU1GmOR8fp2ZO8gyDOIaB/jO2YVVfCP73fSJ96FZMtHZJVlsSNnh8N7ru96PXf1uQtPsydJmcVsTM9jSNugv3yiHq01M+Zt44ff6krIw3zd6RcXSKS/J99uO0iQtxsvX9mbXmf+RBdCCCGalySfzvji/YX0fO5Btl0ewW/5WdywwvGixWJW3HXO37lkVDxX965mbs5mfi9IYVv2dgDcrVYqj5qg4n9Dnye0w/lQXWGs1+kVhC7JQb3QDuLPMSYXEkIcV1FFNdU1VhIPFrAzo4gaq+ZgXhnPXNaz0bLK5mSxakwKSqssvLN6LzszCtmUnkdZlcXeyxju505ppYWSyroEdcrAWAa3DeKez7fbH3vswi4MSghmzqpUTCbFwsRDDn/L3WzC18OVnJJKovw9uKBHJP+Y0MWh53ZjWh5XvmUshH1up1B83M08cXE3Qn2bZu2wsqoadmcW0y7Uh3WpueSVVtE+zKfRMfC1FiYe4qNf09m8L59LekUxe0ofwEiWvtx8AB93V87pGIKPmwvlmzdjDQllbZknzy3ZTWF5Ned0CCH5SAkp2SVU1ViJ9Pfgp5kjyS2pItDblWeX7CbCz4NBbYOJDfLC39OI2X9/TuXTDfsbtOfm4QlcMygWDbQLNSon8kurmD53M5vS8+2v8/Uw8+nNg+jZxkjUCsurKak0ptf3dnPh7dV7mbV4t/31d49uj7e7GYs5k/f23k2fsD5c0f5GKkvaMqRtMMt2ZfLy8mRySowxyRN6RPD3sR3tN1YsVk1uaSVhvkaJclFFNT5uZkwmxa5DRXyxaT/944O4uFcU1RYrfxwu4lBBBYFeruzNKWXrvny+2nKQKQNjuHNUe7SGNoGe9psWWmssVv2X3IgRQghx1pPk82QdyCtj6e+ZhPq6s+Wtt5iy8itm3OZCsScM26UZlx9G3EajjO7I5YWcay5FA3eHhfCztzHRUFx1NTUoPj2USXCva/kwP5G1FYd5ODefdtU1ENoFsv8AnwiYthh+mAl7V8Lwe2Hsk8323YUQp1dljYVVSdksSDzEM5f1xNvNhZVJWfyyJ4cP1qY7vHZyn2i+2+a4BEiIjxs5JVVM6BFBhJ8nUQEePPWjsaTMwPggNqbX9daZFEwblsDozmFcY+s1DvRyZdvj45r2Szrpwa8T+WZrBsvuHcH87YfILq5g3sa6ScfCfN0Z3y2CxTszySmpdHivm9nEuK7htAn0YtqweMJsY0j/jNaaI0WVBHq7kllYwfNLkzhUUM4HUwfi79lwzGxGQTl3fbaVbfsLiA7wJKPAmGW4d0wAQd5u9lLk2vZU1VgJ8XHnnxd14dP1+x3+j9qFeuPtbua3g44TkcUFezFlYCy7DhWxwHazoWO4D56uLiTaXts5wpeckkp7kno0bzcXSqssjT43pG0wn9486IRLy4UQQohjkOTzRGz6/BP8vX3ZtzEZv/nz+LFtXz7uPJl79sxixJ5c3r6tmpC257LgiHHB9snzNbjVwNS/u3BzeSHv+/tRbLsr/PGhTHpXVqEG3Q7n/R+Y3aAsD56zzWjY6UI4tBWKj5olc8ILMPCW0/ithRBnspLKGn5IPERJZQ2ebi5cMzCW9NwyZszbys6MIm4d2ZZHLujS4H1ZRRVUWzXRAZ6UVNZw56dbWZOSg8XqeJxfcd9IQnzcG02oziRpOaWMeuHnBo/HBnmxP6/M/ruLSTFtWDyX94shPsSL8iqjF7lN4Kkv93IqDheWM2vRbpbszLSX+Ib7udMx3JcukX60D/Xh8n5tMJkUB/LKmLdxPyM7hjL7f3tYm5Jr/5x/TOjCgfwySipq+Pek7vbJnpIyi7l73jZySirxdjdTVlVDiI87e3NKCfN1p1dMAJ6uLqxOzuacDqFcNSCGN39OISO/nB5t/BndOYyyKgt5pVUMTAiitLKGgQlBJ73GsRBCCNEIST6Pp7o4m5QBDSft2N1GEZel+aON4uo7J+By4QukFqQyaf4kYrI0Q/+w8sUIk33c4XkhfRl4OImre90C/ac1HI9YUWis2amUMXmO1vDLi7D3Z+j7N+h19Wn4tkKIs0G1xYrZpE563PEbK1P4ZstBbhwWz/VD4pumcU3guSW7+eG3w9w5qh1b9uUT5uvBved1ZGdGIfHB3ny77SDju0U0mPymOWmtKSir5qAt6Tseq1WTnltKm0AjqW4fduwZtC1WoxS2fnn5qW4TQgghxF9Iks/j2bR6IT7T69aJ29RBMWCPpjTCj8Iod6Iikuky/X3oPAGAP3L/YHv2dspryhkePZz0wnQ6BHY45lptQgghhBBCCNEKnFDy2arXiRgw4mJSXs+k4MGX8C6D4n5ldOmXD74aUKCCoEPdwuRdgrvQJbiu1K1jYMdmaLUQQgghhBBCtDytfgq79mNvod+S+cSPy+ZObLMW+kaAixkG3w4uZ/aYKCGEEEIIIYRoCVp1z2ctFdYRzyc2GGMyywsgum9zN0kIIYQQQgghziqSfNYKbtfcLRBCCCGEEEKIs1arL7sVQgghhBBCCNH0JPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHkJPkUQgghhBBCCNHklNa6af+AUtnAvib9I84JAXKauxEtmMTPeRJD50kMnScxdJ7E0HkSQ+dJDJ0nMXSOxM95LTGGOVrr84/3oiZPPs90SqnNWuv+zd2Olkri5zyJofMkhs6TGDpPYug8iaHzJIbOkxg6R+LnvLM5hlJ2K4QQQgghhBCiyUnyKYQQQgghhBCiyUnyCW83dwNaOImf8ySGzpMYOk9i6DyJofMkhs6TGDpPYugciZ/zztoYtvoxn0IIIYQQQgghmp70fAohhBBCCCGEaHKSfIo/pZRSzd2Glk5iKIQQ4q8k5xUhREt1ViefSinPej/LgfoU6Hp12RJD50kMT43EzXlKqTillFtzt6MlU0r5KqXO6vNmU1JKDVRKhdl+ljieAqXUNKVUvJYxU6dMKRXY3G1o6ZRSVymlXqrdn8XJU0pFKKXMtp9b1TXOWXnwV0oNUEptAN5SSj0BjkmUOD6l1CCl1FKl1HNKqZtBYniylFI9lFJbgeeVUneAxPBkKaVMSqm7gam231vVAfqvoJTqpZRKA74BvlJK+TR3m1oapVQbpdSXwGvAO7IdnjylVCTwJDAFQGttbdYGtTC2c/Ia4AnAT7bBU6OUegT4r+3ns/IauCkppYYopX4F3gCGAgXN3KQWx3ZO3gV8AsxVSrm1tmvDs27Hs53g3gQ+Al4EblNKXWZ7Tg7WJ0Ap1R54C1gIbAEeV0pdaXvurNtmmoJSygW4FfgaeB24Wik1uXlb1SL5AzcBY5VSYa3tAO0spZQrcD/GSW4MEA3cbntOjocnbhTwG/AM0Ae4A+R4eJLyMWI3TinVCyR+J0op1RFYCXyitY7TWv9WeyyU/fjE1ItTDrDD9rOcT06AMrgopR4G5gMfa61DgINAz+ZtXcuilPLGOCe/CpwHxGNcK9ZeN7YKZ+OB3wysx9g5EoHngLEgvU4noS3wi9b6da31Fxh3qx8EuVt9orTWFmAQkKy1TgceA6YopXo0a8NangAgGziMkYSKk+MGtAF+0loXAo9jSz7leHhSrgSytda7gVnAZSDHwxNlu/APBTYBvwDTwIifJE/Hp7VOBlZj3AxGKXW9Uqqv7TnZj09OWyBGKTUIuEQp1a41XfSfCm2wAL8C0VrrOUopLyADqGze1rU4ZYAH8Ltt330JW2WXLcatQotPPpVSlyql1iml7lRKDcX4j3XHlnAC3YFkpVR8MzXxjFcvhncppfphlFFcWO8lVUCpUiqqeVp45lNKhSmlHq1NLm13t1YAAUopF631amAnMFkpFdycbT1T1Yth93oPa4wT3gagp1Kqt+21csHaiKO3Q5sngQ22mCUBO5VS4c3SwBbgGDF8FqPnCaA/kG0734ijHL0fK6VMtousciACI/k0K6VGg3FhK/uzo2Nsg/8FZimlkoHpGOXfzykZx92oRs4ntQnmAWACRu/TA8A7SDVIo+rFsCeA1nq11rratk+XAZ2BdrbXtvh8oik0sh16YZxLrlZK+QFRQKJSamhr2pdb9MailIoG/g68DGQCrwAKWARca6upboNx0ltpS6xEPUfF8DDGCS4ZyFNKvaeMsYqXYJRW5DZbQ898XYG7gXMAtNalGD12bYFY22s+wOgNbdccDWwBulEvhgBa63St9eMYd/33AtfaHpe7/Y1rbDvcpLWusMUsHOigtT7SjG080znE0GaL1jrZNqwjEKME90ul1OW20mZRx2E/tvVumjDOxXu11muBH4C7lFLvKKUiZX9uoHYbHF7vsSygGnhTaz0cuA4YgVG6Jxo6ejussT0eDbgCT2GcT17HKAWPke2wgdoYDqt94KgE/TtgCEgVyJ+ojeEIsJ+TfwB8MK5rJgE/YVQl3WJLSM96LS75VLaZoWy8MC4EftJafwN8Czyntf4eo0x0HXC+1noOMBd41PYZrfru1nFi+B1GT8l1tudGAIeAfUDv09vSM9dRMQTj7lUaEKuUqu11/wbjYr+/UspHa33A9pq7Tl9Lz1yNxDASIz5xSqlRtteYALTWmRg9JhFKqQn1n2vNjrMd1vYsldV73opxc6n2/a36WAgnFkOgAkBrfVhrPV1r/R/gaeA6rXX16WvtmedE9mPbhWk2UKSM2TGvA8YDvlrrw619X/6TbTBOKTXG9lgy8Cnwta2a5g9gI3Db6WvpmetEtkOb9RjVXUe01vuAXRj7d8xpaegZ7ERjWC/RtGKbcKi178O1/iSGsbX7stZ6P8Z14C7gMq31pxjzrJyHUbl51mtRG4tS6n5gs1LqfqXUEKAU4w50GwCt9TNAlFJqItAXY7xT7XIru4FApZRXa767dQIxnIVx17W91noKcCPGBE5HgJRmafQZ5qgYjrQ9XIwxuZAGhiul/G1jPX8C+gF/s70uA6NXuVVf9B8jhkXUxfBcpZSvrdektlxqE7AdmKSU8m7td1pPYDscoZTytb229ljfFiMJQCn1EHCfMsbutEonGsN6k7t42qpFsL3GWxkl9q3SCcRvZO02iFE9MxzYCtRgzHprUUrFteZ9+QRieI5Syk9rnYuRfB6pNzZsF5DT2i/8T3A7rO1RysbocZpo+30PEIdRPddqnei+bCuTrz0nJwHXgPR8wgnvy7XHw3iM6+/+tt+zgI60sLzsVLWYL6mUisMo/5yOMcPW0xjltK4YY8FqS5/+i1FGugijp+5VpdRTwGyM3r2yoz+7tTiJGL6OUQKArVwvGfCjbidptY6K4QHgP7ZEc6HW+kVgDUZv5zjbW77C6E2eoZT6ACOZX9fKb4AcK4Y/1IthGLYY1l5o2S6+NmDMgDuysc9uLU52O6x3YTAA6KyU2oIxic6i1npMPIkYnmd7vQLaA58qpZ61Pb8WY56BVuck4jfe9pZfbI9doLW+Afgfxnm6/LQ3/gxxstsgxrjFR5RSDyqlbgXuA5a15gv/UzgnbwEWALcqpZ4Gfse4HspprTeFT+F8UntOXgWUK9tyfK3ZKRwPUzB63B9RSs3BqJT7BSg87Y1vBupMvgZWSnUGbgA2A6kYZbXtbb0hL2OUoVRgDB5/RGudYnvf7xg11oXAZIya/zla689O/7doXk7EcDvwvNb6U9ud/nuA2Vrrg83xPZrTcWL4PMadrf9qrbOVsYbivRgJ0mu2sh6UUjEYvcs+WuvlzfE9mpMTMXxVa33AVmZmUUp5AGG2spVWxdkY2j5jFsYNkDu11t82w9doVk7EcLbWer9Syh1jjNNgIF1r/XmzfJFm4kT83tBapx31WabWmDQ5ez5RSo3AqOyaDLxtK9lrVf6ic3IPjKV/Sm1DjlqVv+CcbMJYXeIaIFFrva1ZvkgzciKGr2ut05VS7TDWSp0AzG9N55MztudTKXUBRnlOOMbC3ldjlJzUzjD4HMZFQCrGmMQrlVIjbeUASYCn1nqz1vofWusRrTTxdCaGqRg7DlrrDK31g6008TxeDF8EOgADlVKuWusSjFlu3ai7w4XW+oDWel0rTTydieEF4HCntaKVJp5Ox9DmTa11ZCtNPP+K7bBSa/2z1vqZ1nShAE7H77x6n1M7jrs1Jp5/xTa4Wmv9itZ6ZCtNPJ2J4fm1n6O13qG1/riVJp5/xXZo1VpXaa0/bKWJp9PXhlrrVK31XK31lNZ2Pjljk09gNPCy1noaxni5azHW/ItSxnivwxglT1dh/CfnAB9jlNd2QMYngnMx7IiRxLd2x4thJvAzxoHHCqC1/hVjbOcApVRso5/aukgMnedsDONsjx1ohrafKZyJYX/ZDv+a/bg1Jp31OBPDfrINArIf/xXknOw82Q6dcMaW3SqlpgJ5wAKttVZKLcUoo00Fvtdab7C97gBwhdZ6vVKqP8aYnGSt9dbmavuZQmLovJOI4T5giu3gUltm29ov9gGJ4V9BYug8iaFzJH7Okxg6T2LoPImh8ySGzjl6SuAzySIg3/afGgJUAv+HsSbOxbaxX5sxZmr1BtBab7Y9JgwSQ+edaAx3Ah61b2rtB5ajSAydJzF0nsTQORI/50kMnScxdJ7E0HkSQyecscmnrrcIutY6RxmT3rgA72IMzv0YY2aoYGBHszTyDCcxdN5JxnBnszTyDCcxdJ7E0HkSQ+dI/JwnMXSexNB5EkPnSQydc8aW3danlErAWCalne33eIyFW0OArVrrjOZrXcsgMXSexNB5EkPnSQydJzF0jsTPeRJD50kMnScxdJ7E8OSdsT2fR1HAOqXUeOAZjDV0rtdaFzRvs1oUiaHzJIbOkxg6T2LoPImhcyR+zpMYOk9i6DyJofMkhieppSSfPTHWEhqCscbQ7GZuT0skMXSexNB5EkPnSQydJzF0jsTPeRJD50kMnScxdJ7E8CS1lLLbbsBFwCta68rmbk9LJDF0nsTQeRJD50kMnScxdI7Ez3kSQ+dJDJ0nMXSexPDktYjkUwghhBBCCCFEy2Zq7gYIIYQQQgghhDj7SfIphBBCCCGEEKLJSfIphBBCCCGEEKLJSfIphBBCCCGEEKLJSfIphBBCCCGEEKLJSfIphBBCnAKl1JNKqXOP8VxvpVTv09wkIYQQ4owmyacQQgjx1+tt+yeEEEIIG3NzN0AIIYRoKZRSgcBXgAuggM1KqSWAN5CitZ6qlJoFTLa9/m9a6zFKKS/gYyAM2KG1vrN5voEQQgjRfKTnUwghhDhx04EftNajgGogEngNGAvEK6XCtdaPAM8Az2itx9R7306t9QggUinVsxnaLoQQQjQrST6FEEKIE5cAJNp+3oyRgN4MfAoEAZ7HeF8nYLJS6megLRDdtM0UQgghzjySfAohhBAnbj/QzfZzb+Am4GtgClBa73XlgBeAUkoBScArWutzgcdsnyOEEEK0Kkpr3dxtEEIIIVoEpVQIxphPBbgCS4ErgXyMcaAPaK3XKqWCgC8xekIfAbYAHwARQBFwjda66PR/AyGEEKL5SPIphBBCCCGEEKLJSdmtEEIIIYQQQogmJ8mnEEIIIYQQQogmJ8mnEEIIIYQQQogmJ8mnEEIIIYQQQogmJ8mnEEIIIYQQQogmJ8mnEEIIIYQQQogmJ8mnEEIIIYQQQogm9//fuq8+zZFqVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#以第一交易日2009年1月5日收盘价为基点，计算净值\n",
    "df_new=df/df.iloc[0]\n",
    "#将上述股票在回测期间内的净值可视化\n",
    "df_new.plot(figsize=(16,7))\n",
    "#图标题\n",
    "plt.title('股价净值走势',fontsize=15)\n",
    "#设置x轴坐标\n",
    "my_ticks = pd.date_range('2008-01-01','2019-01-18',freq='Y')\n",
    "plt.xticks(my_ticks,fontsize=12)\n",
    "#去掉上、右图的线\n",
    "ax=plt.gca()\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 累计收益率和年化收益率\n",
    "收益率可以根据上面公式计算，或使用对数收益率，也可以根据上面的累计净值来推出累计收益率（累计净值-1）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计收益率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上证综指</th>\n",
       "      <td>0.380328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>8.962982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>1.474747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>3.788620</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         累计收益率\n",
       "上证综指  0.380328\n",
       "贵州茅台  8.962982\n",
       "工商银行  1.474747\n",
       "中国平安  3.788620"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 区间累计收益率(绝对收益率)\n",
    "total_ret=df_new.iloc[-1]-1\n",
    "TR=pd.DataFrame(total_ret.values,columns=['累计收益率'],index=total_ret.index)\n",
    "TR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年化收益率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上证综指</th>\n",
       "      <td>0.033520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>0.265105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>0.097122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>0.173761</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         年化收益率\n",
       "上证综指  0.033520\n",
       "贵州茅台  0.265105\n",
       "工商银行  0.097122\n",
       "中国平安  0.173761"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###年化收益率,假设一年以250交易日计算\n",
    "annual_ret=pow(1+total_ret,250/len(df_new))-1\n",
    "AR=pd.DataFrame(annual_ret.values,columns=['年化收益率'],index=annual_ret.index)\n",
    "AR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最大回撤\n",
    "实际上，numpy和pandas借助库函数均可以实现一行代码计算最大回撤。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy方法计算结果：52.3%\n",
      "pandas方法计算结果：52.3%\n"
     ]
    }
   ],
   "source": [
    "#numpy:np.maximum.accumulate计算序列累计最大值\n",
    "code='上证综指'\n",
    "n_d=((np.maximum.accumulate(df[code])-df[code])/np.maximum.accumulate(df[code])).max()\n",
    "#pandas使用cummax（）计算序列累计最大值\n",
    "p_d=((df[code].cummax()-df[code])/df[code].cummax()).max()\n",
    "#打印结果\n",
    "print(f'numpy方法计算结果：{round(n_d*100,2)}%')\n",
    "print(f'pandas方法计算结果：{round(p_d*100,2)}%')                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>最大回撤</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上证综指</th>\n",
       "      <td>0.5230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>0.5331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>0.3444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>0.5070</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        最大回撤\n",
       "上证综指  0.5230\n",
       "贵州茅台  0.5331\n",
       "工商银行  0.3444\n",
       "中国平安  0.5070"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#定义成函数，减少重复工作\n",
    "def max_drawdown(df):\n",
    "    md=((df.cummax()-df)/df.cummax()).max()\n",
    "    return round(md,4)\n",
    "md={}\n",
    "for code,name in stocks.items():\n",
    "    md[name]=max_drawdown(df[name])\n",
    "#最大回撤率结果：\n",
    "MD=pd.DataFrame(md,index=['最大回撤']).T\n",
    "MD"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### alpha和beta \n",
    "使用回归来估计alpha和beta的值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>上证综指</th>\n",
       "      <th>贵州茅台</th>\n",
       "      <th>工商银行</th>\n",
       "      <th>中国平安</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-06</th>\n",
       "      <td>0.030004</td>\n",
       "      <td>0.003046</td>\n",
       "      <td>0.028007</td>\n",
       "      <td>0.035084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-07</th>\n",
       "      <td>-0.006783</td>\n",
       "      <td>-0.017654</td>\n",
       "      <td>-0.021885</td>\n",
       "      <td>0.000309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-08</th>\n",
       "      <td>-0.023820</td>\n",
       "      <td>0.016285</td>\n",
       "      <td>-0.021918</td>\n",
       "      <td>-0.051250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-09</th>\n",
       "      <td>0.014205</td>\n",
       "      <td>-0.011425</td>\n",
       "      <td>0.011204</td>\n",
       "      <td>0.002522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-12</th>\n",
       "      <td>-0.002368</td>\n",
       "      <td>-0.012852</td>\n",
       "      <td>-0.005540</td>\n",
       "      <td>-0.017609</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                上证综指      贵州茅台      工商银行      中国平安\n",
       "date                                              \n",
       "2009-01-06  0.030004  0.003046  0.028007  0.035084\n",
       "2009-01-07 -0.006783 -0.017654 -0.021885  0.000309\n",
       "2009-01-08 -0.023820  0.016285 -0.021918 -0.051250\n",
       "2009-01-09  0.014205 -0.011425  0.011204  0.002522\n",
       "2009-01-12 -0.002368 -0.012852 -0.005540 -0.017609"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#计算每日收益率\n",
    "#收盘价缺失值（停牌），使用前值代替\n",
    "rets=(df.fillna(method='pad')).apply(lambda x:x/x.shift(1)-1)[1:]\n",
    "rets.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>alpha</th>\n",
       "      <th>beta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>0.246</td>\n",
       "      <td>0.637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>0.083</td>\n",
       "      <td>0.614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>0.153</td>\n",
       "      <td>1.071</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      alpha   beta\n",
       "贵州茅台  0.246  0.637\n",
       "工商银行  0.083  0.614\n",
       "中国平安  0.153  1.071"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#市场指数为x，个股收益率为y\n",
    "from scipy import stats\n",
    "x=rets.iloc[:,0].values\n",
    "y=rets.iloc[:,1:].values\n",
    "AB=pd.DataFrame()\n",
    "alpha=[]\n",
    "beta=[]\n",
    "for i in range(3):\n",
    "#使用scipy库中的stats.linregress线性回归\n",
    "#python回归有多种实现方式，\n",
    "#如statsmodels.api的OLS，sklearn库等等\n",
    "    b,a,r_value,p_value,std_err=stats.linregress(x,y[:,i])\n",
    "    #alpha转化为年化\n",
    "    alpha.append(round(a*250,3))\n",
    "    beta.append(round(b,3))\n",
    "AB['alpha']=alpha\n",
    "AB['beta']=beta\n",
    "AB.index=rets.columns[1:]\n",
    "#输出结果：\n",
    "AB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "贵州茅台beta:0.637\n",
      "工商银行beta:0.614\n",
      "中国平安beta:1.071\n"
     ]
    }
   ],
   "source": [
    "#使用公式法直接计算beta值（见前文公式）：\n",
    "beta1=rets[['上证综指','贵州茅台']].cov().iat[0,1]/rets['上证综指'].var()\n",
    "beta2=rets[['上证综指','工商银行']].cov().iat[0,1]/rets['上证综指'].var()\n",
    "beta3=rets[['上证综指','中国平安']].cov().iat[0,1]/rets['上证综指'].var()\n",
    "print(f'贵州茅台beta:{round(beta1,3)}')\n",
    "print(f'工商银行beta:{round(beta2,3)}')\n",
    "print(f'中国平安beta:{round(beta3,3)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "贵州茅台alpha:0.244\n",
      "工商银行alpha:0.077\n",
      "中国平安alpha:0.138\n"
     ]
    }
   ],
   "source": [
    "#使用公式法直接计算beta值（见前文公式）：\n",
    "#annual_ret是前文计算出来的年化收益率\n",
    "alpha1=(annual_ret[1]-annual_ret[0]*beta1)\n",
    "alpha2=(annual_ret[2]-annual_ret[0]*beta2)\n",
    "alpha3=(annual_ret[3]-annual_ret[0]*beta3)\n",
    "print(f'贵州茅台alpha:{round(alpha1,3)}')\n",
    "print(f'工商银行alpha:{round(alpha2,3)}')\n",
    "print(f'中国平安alpha:{round(alpha3,3)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 夏普比率和信息比率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>夏普比率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上证综指</th>\n",
       "      <td>0.398217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>2.547269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>1.215739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>1.737360</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          夏普比率\n",
       "上证综指  0.398217\n",
       "贵州茅台  2.547269\n",
       "工商银行  1.215739\n",
       "中国平安  1.737360"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#超额收益率以无风险收益率为基准\n",
    "#假设无风险收益率为年化3%\n",
    "exReturn=rets-0.03/250\n",
    "#计算夏普比率\n",
    "sharperatio=np.sqrt(len(exReturn))*exReturn.mean()/exReturn.std()\n",
    "#夏普比率的输出结果\n",
    "SHR=pd.DataFrame(sharperatio,columns=['夏普比率'])\n",
    "SHR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>贵州茅台</th>\n",
       "      <th>工商银行</th>\n",
       "      <th>中国平安</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-06</th>\n",
       "      <td>-0.026958</td>\n",
       "      <td>-0.001997</td>\n",
       "      <td>0.005079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-07</th>\n",
       "      <td>-0.010871</td>\n",
       "      <td>-0.015102</td>\n",
       "      <td>0.007092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-08</th>\n",
       "      <td>0.040105</td>\n",
       "      <td>0.001902</td>\n",
       "      <td>-0.027430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-09</th>\n",
       "      <td>-0.025630</td>\n",
       "      <td>-0.003001</td>\n",
       "      <td>-0.011683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-12</th>\n",
       "      <td>-0.010485</td>\n",
       "      <td>-0.003173</td>\n",
       "      <td>-0.015242</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                贵州茅台      工商银行      中国平安\n",
       "date                                    \n",
       "2009-01-06 -0.026958 -0.001997  0.005079\n",
       "2009-01-07 -0.010871 -0.015102  0.007092\n",
       "2009-01-08  0.040105  0.001902 -0.027430\n",
       "2009-01-09 -0.025630 -0.003001 -0.011683\n",
       "2009-01-12 -0.010485 -0.003173 -0.015242"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###信息比率\n",
    "#超额收益率以指数收益率或其他为基准\n",
    "#这里以上证综指为基准\n",
    "ex_return=pd.DataFrame() \n",
    "ex_return['贵州茅台']=rets.iloc[:,1]-rets.iloc[:,0]\n",
    "ex_return['工商银行']=rets.iloc[:,2]-rets.iloc[:,0]\n",
    "ex_return['中国平安']=rets.iloc[:,3]-rets.iloc[:,0]\n",
    "ex_return.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>信息比率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>2.440970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>0.931029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>2.124666</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          信息比率\n",
       "贵州茅台  2.440970\n",
       "工商银行  0.931029\n",
       "中国平安  2.124666"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#计算信息比率\n",
    "information=np.sqrt(len(ex_return))*ex_return.mean()/ex_return.std()\n",
    "#信息比率的输出结果\n",
    "INR=pd.DataFrame(information,columns=['信息比率'])\n",
    "INR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计收益率</th>\n",
       "      <th>年化收益率</th>\n",
       "      <th>最大回撤</th>\n",
       "      <th>alpha</th>\n",
       "      <th>beta</th>\n",
       "      <th>夏普比率</th>\n",
       "      <th>信息比率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上证综指</th>\n",
       "      <td>0.380</td>\n",
       "      <td>0.034</td>\n",
       "      <td>0.523</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.398</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国平安</th>\n",
       "      <td>3.789</td>\n",
       "      <td>0.174</td>\n",
       "      <td>0.507</td>\n",
       "      <td>0.153</td>\n",
       "      <td>1.071</td>\n",
       "      <td>1.737</td>\n",
       "      <td>2.125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>工商银行</th>\n",
       "      <td>1.475</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.083</td>\n",
       "      <td>0.614</td>\n",
       "      <td>1.216</td>\n",
       "      <td>0.931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵州茅台</th>\n",
       "      <td>8.963</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.533</td>\n",
       "      <td>0.246</td>\n",
       "      <td>0.637</td>\n",
       "      <td>2.547</td>\n",
       "      <td>2.441</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      累计收益率  年化收益率   最大回撤  alpha   beta   夏普比率   信息比率\n",
       "上证综指  0.380  0.034  0.523    NaN    NaN  0.398    NaN\n",
       "中国平安  3.789  0.174  0.507  0.153  1.071  1.737  2.125\n",
       "工商银行  1.475  0.097  0.344  0.083  0.614  1.216  0.931\n",
       "贵州茅台  8.963  0.265  0.533  0.246  0.637  2.547  2.441"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将上述指标合并成一张表\n",
    "indicators=pd.concat([TR,AR,MD,AB,SHR,INR],axis=1,join='outer',sort='False')\n",
    "#结果保留三位小数\n",
    "indicators.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_max_drawdown(df,name):\n",
    "    #累计收益率\n",
    "    df_new=df/df.iloc[0]\n",
    "    total_ret=df_new.iloc[-1]-1\n",
    "    #年化收益率,假设一年以250交易日计算\n",
    "    annual_ret=pow(1+total_ret,250/len(df_new))-1\n",
    "    \n",
    "    #最大回撤\n",
    "    dd=(df[name].cummax()-df[name])/df[name].cummax()\n",
    "    # 区间最大回撤对应的索引值\n",
    "    j=dd.idxmax()\n",
    "    # 区间最大值对应的索引值\n",
    "    i =df[name][:j].idxmax()\n",
    "    #最大回撤比率\n",
    "    d=dd.max()\n",
    "    \n",
    "    #计算beta和alpha\n",
    "    beta=rets[['上证综指',name]].cov().iat[0,1]/rets['上证综指'].var()\n",
    "    alpha=(annual_ret[name]-annual_ret[0]*beta)\n",
    "    \n",
    "    #夏普比率\n",
    "    #假设无风险收益率为年化3%\n",
    "    exReturn=rets-0.03/250\n",
    "    sharper_atio=np.sqrt(len(exReturn))*exReturn.mean()/exReturn.std()\n",
    "    \n",
    "    #信息比率\n",
    "    ex_return=rets.loc[:,name]-rets.iloc[:,0]\n",
    "    information_ratio=np.sqrt(len(ex_return))*ex_return.mean()/ex_return.std()\n",
    "    \n",
    "    ###绘制图像\n",
    "    #设置图片显示大小\n",
    "    plt.figure(figsize=(16,6))\n",
    "    #对原时间序列画图\n",
    "    df[name].plot()\n",
    "    #画出最大回撤的高低点，红色圆圈\n",
    "    plt.plot(df[name][[i, j]],'o', color=\"r\", markersize=10)\n",
    "    #添加文本说明\n",
    "    TR=round(total_ret[name]*100,2)\n",
    "    AR=round(annual_ret[name]*100,2)\n",
    "    MD=round(d*100,2)\n",
    "    A=round(alpha*100,2)\n",
    "    B=round(beta,2)\n",
    "    S=round(sharper_atio[name],2)\n",
    "    I=round(information_ratio,2)\n",
    "    # xy=(j,df[name][j]),xytext=(i,df[name][i]), \n",
    "    plt.annotate(f'累计收益率：{TR}%，年化收益率：{AR}%\\n 最大回撤：{MD}% \\n alpha:{A}，beta：{B}\\n夏普比率：{S}，信息比率：{I}',\n",
    "          xy=(j,df[name][j]),xytext=(i,df[name][i]), \n",
    "          bbox = dict(boxstyle = 'round,pad=0.5',\n",
    "          fc = 'yellow', alpha = 0.5),\n",
    "          arrowprops=dict(facecolor='red', \n",
    "          shrink=0.05),fontsize=12)\n",
    "    #添加标题\n",
    "    plt.title(name+'量化回测指标',fontsize=15)\n",
    "    #设置X轴标签\n",
    "    my_ticks = pd.date_range('2008-01-01','2019-01-18',freq='Y')\n",
    "    plt.xticks(my_ticks,fontsize=12)\n",
    "    #不显示X轴标题\n",
    "    plt.xlabel('')\n",
    "    #将右边 上边的两条边颜色设置为空\n",
    "    ax=plt.gca()\n",
    "    ax.spines['right'].set_color('none')\n",
    "    ax.spines['top'].set_color('none')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#贵州茅台买入持有策略回测可视化\n",
    "plot_max_drawdown(df,'贵州茅台')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#贵州茅台买入持有策略回测可视化\n",
    "plot_max_drawdown(df,'工商银行')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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p+BQRERERkTqFI5b2WWkc3qcjKwpKk86VVobjt1cWlAEJwafPW+Na9ZXdvjhnHQD528p+0Jyl9VHwKSIiIiIidQpHo6R5PPTrks2qrclB4erCctJ9TlgRiTqBZSDsrPmMHY8xBoINzGhuKw3+0GlLK6PgU0RERERE6hSJWrxeQ9fcdLaVBYlGLfPW7uB3L31LeSBM+8w0wCnPBQiEYplPJ9w4e/g+AHTJSW/wVislCRlVaRsUfIqIiIiISJ1CEUuax9AuMw1rncDwvEdn8dLcdWwrC5KR5pTXxrriBsJR/D5PvBnRbafsz/Tfj6Vbu4waW7XUpiSgpkNtTc32UyIiIiIiIgnCkSg+ryee4SyqCFEWdEprK0MRMtzGQoFQlMpQhEA4klRym53uIzvdR5rXNHirlVJlPtucejOfxpgrjTFT3a95xphHjDGPG2NmGmNubY5JioiIiIhIywlHLT6PYa/2mQCs3V4eP1cWiMQbC/3l3e8Z/If33YC0ZrOhNK+nzjWfsa1aAIINzJDK7qPe4NNa+7C1doy1dgwwHVgBeK21I4F+xpiBTTxHERERERFpQeGoxec19O2SDcCawqrgs6giFM98xhRXhsnNqFlk6fd56lzzWe5mUwFttdIGNXjNpzFmb6Ab0BN40T08BRjVBPMSEREREZFWwFrrNBzyeMhwS2kTS2dLA+EaWc7vNxaT5a+Z+fR7PXWW3ZYFqkptG9qYSHYfjWk4dDXwMJANrHePFeIEpEmMMROMMXOMMXMKCgp++CxFRERERKRFxDrYpnkMaW7wGdtKJab6fp4rC8r4bn1xjWuleevOfJYlZD4b2phIdh8NCj6NMR5gLDAVKAUy3VM5qa5hrZ1krR1urR3epUuXXTRVERERERFpbmE3CPR5Pfi9zq/+BSWBpDF+n8FtbBvXt3N2jWs5Zbe1B5WJmc9wVJnPtqahmc/RwJfWWQE8l6pS24OA/CaYl4iIiIiItAKxINDnMfHg890Fm5LGeD0eqsWeXDqqb41rpdVRdmut5fuNVdlSZT7bnoZutXIC8Jl7+3VgujGmB3ASMKIpJiYiIiIiIi2vKvNp8HgMPo9h/Y6KpDFpHkO0WqyYuNVKjN9nau12e+vr3/Hsl2vi97Xms+1pUObTWnuztfZV93YxMAaYBYy11hY13fRERERERKQlhWKZTzfrmeatGUL4vNXznrUEn9XWfD42fSXH/30apYFwUuAJCj7bosY0HIqz1m631r5ord1U/2gREREREdldFVc46zB9HifA9KcIKjvnpNc4lir4TPN6CLlltyWVISa+8z1LN5cyJ7+wxthwKy+7tdZyy2sLUs5dUtup4FNERERERPYMlzz1FVDVDCgx89m9XQYAFx/VJ34sLysNcNaBVpfm88TLbgvLgvHj67Ynl/H2aJ9Ra3luaxEIR3n2yzWc+Z+ZLT2V3YaCTxERERERSSkYjrK20AkMA27GMjGjecepB/DVzcfSNTcjfmxkv04AbCtN7ogLsa1WLNbaeEbVGRtMGtc+y590vjVava085fH8rWUs3lRzmxlpeMMhERERERHZw0xfVhC/HQs+0xLWd+ak++jqZj+fv3wET85YxZ0/PZC8rDTGD92rxvVigWsoYtlWVhWcJt4G6JTtp7CsZvDampz32Jcpj4+5dyoA+XePb8bZ7B4UfIqIiIiISErlwUj8dmyLlMQ1n76EEtyR/Tsxsr+T9bzr9KEprxcLXIORKC/NXRc/XlQRShrXMdvPuu2pM4utwcINRWxNyOwGw9GUa2Elmd4hERERERFJKZKwf0os+LQJfYBSdbmtS2y96Hfri3h3wUZOdrOjb8zbkDSuY7afbWXBGo9vLe79YEnS/bUpAuUlm0roc+M7zFu7o7mm1eop+BQRERERkZTCCcHnTw/ZGyAp49dYsezg/VOWkpXm5aoxA1KO65jtp6QyHA94W5vu7TOS7q/eVlZjzLy12wF44vNVzTKn3YGCTxERERERSSnqBp8zbhzHgT3bA7C9vKpENtYBt6Fi27V8lV/I/x3Ri27tam7RAk7w6TxX68x+RqPQOcfPrJuOBWDV1nL3eFWw3inbeW1vfruh1QbRzU1rPkVEREREJKVY5jMWNFbXrV1GyuO18Ziq6/TqmFVjneRzlx9B19x0lm0uBZwuuI19juYQikZJ93np1i6d3Awf+VudzGdpsCoYn/jOovjtpZtLGLJ3+2afZ2ujzKeIiIiIiKQUiToZO2+K4PPzG8ayb7fcRl0v8Tp+nydpz9DRAztzZP/ODOiaG898bi6pBODpmfnMWL61sdNvMuGIJc1rMMbQt3M2+W7ZbVFCVjg/YSuWzxK6Bu/JFHyKiIiIiEhKdWU+e3bIavT1EoPPdJ8Xf0LwmZHmjd8evFc7AL5Z7aybvO2NhbVubdISwtFovNNv707ZrHIznzvKQynH/+39JSmP72lUdisiIiIiIinFut0mBo2f3zA2aQuWxqie+fQk3M/LTIvfbp+ZRkaah8pWulYyGLbxrG3fTlm8M38DgXCEHRWp16ieeEB3AuEIG3ZU0rdzdnNOtVVR5lNERERERFKqynxWhQ09O2Q1utw2xpuw5jOW9czNcPJhV41N7nyb5vEQirTO4DMcjcb3LO3TOZuohbWFFTX2KwVnb9P0NA/nPfolY++dmtSUaE+jzKeIiIiIiKQUy3x6dlHKylMt8wmw4PYTCIajNZoP+byGcKR1BmrhiI2XIvdxM5n5W8uoDNUMlrPTfVQEI8xxS4gD4SiZfm+NcXsCZT5FRERERCSlWPDn20XRZ2LmMz0h2KweeAL4vB7C0eRgLtIKsobWWj5fvpWv1+wAoG8nJ/ictrSAsJup3TsvMz4+2+9jyqLN8fuBcIRwJBrvkLsnUfApIiIiIiIpxbrd1rLTSqNVX/NZlzSPIRSxSQFncYqy1uYWqLYOtYPbmfeZWasJuXNtn7B+NTs9OctZGYry3FdrGHPvVOa62dA9hYJPERERERFJKRx1ykuN2TXRZ6qy29pELWwurkxa97m9PMgNL8/nT28t3CXz2RkVdTRb2lRUAVStY4XkLr7gZD5jQeeyzSVNMMPWS8GniIiIiIikFInalHt87qzaym5T2VRcyfRlWwkmBZ8hXpizlidn5O+yOTVWecgJPv96xoHxYw+eczAAhWVOt9t2CZnPsw/bJ+nxlaFovJx5RyvI5DYnBZ8iIiIiIpJSIEUjoB8icemo39uwpjuVCZnG7WWptzKp8/GhndsWJtHqbWWcM2kmJZWheOYzMaMZ69z7/FdrgeSy23MO65V0rYpQ1ZYshTvxenZnCj5FRERERCSlQDhao2z0h0jKfKY1LBRZU1gev72tLNCo5/tk8WYG/+F9vltf1KjHVXfvlKXMWlnIJ4u3xIPZzIT3xedNfi3tMpzgMzfDVyNzPHf1dhZuKAagLBD+QfPa3Sj4FBERERGRlMoC4XhWb1dIajjUwOt+uaowfntraeMyhf9zM5HLtuy6tZXlbuYzy1+1rtPnTQ4w22U653LSne8fXXc0T1w8HJ/H8Oe3F7Gj3Cm3rWv9aFukfT5FRERERKQGay1vfrthl16zMQ2HYmau2EZGmgeDYWtp4zKfsc60FcGa+2/urEUbnCxqpr9q/r5q2c1Y0Bl7jQO65jKgay4dsv0UlFS9hvI9LPhU5lNERERERGoIRXb9npqJZbf1BZ8vXjESgM+Xb2W/vdrRrV16ozOf05YWALCtkUFrdbFZby6u5Pa3FgHJaz6r74Oa7Qaf1YPSDllpSfc3FFVwyj8+Z2VB6Q+a3+5CwaeIiIiIiNRQsQsa9VSXWHZbPTCr7rA+HeiSmw7AkB7t6ZSTztJNVeWz1tYdHCee3/YDGvvMzi+Mr/PcXl7VnbaustssvxOYplUrLd5Rntzddv66IhasL+Jfn67Y6fntThR8ioiIiIhIDbNWbmuya/t9nnr3DjXGcFDPPAAO6NGOzjl+liTsi1lXZvbVr9fR96Z34/d3NvhcUVDKz/4zkymLNgPw8NSqIDGx4VD1ODgWmFbfTmaLW3L7zM8P56ox/ePHG9p8aXe3Z7xKERERERFpsPs/XMoVz8wF4JfjBuyy6+a5Zae3jt+vQeOvGTeAMYO68KP9u9E5Jz3pXChS+zrO6178Nun+zpbdriooq/Vcpj8x+EyOPmvLfP7h5P05aJ88Rg/swk8O7hE/viubOrVme8arFBERERGRBqkIRnjo42Xx+93bZ+yya/fskMV3fzqBC0f2adD4g/fJ46lLDqdTTnrS3plQFXzOzi9k0K3vkb81daDo93nY1si1ojErt6Zei3nJUX2S5hNNiD1/d8KgeCa0evD581F9eePqowAY0CUnfrxdtdfWVin4FBERERGRuDe/XQ/AkL3bcWT/TowZ1HWXXj/WCbaxqgdyQTf4fO7LNQTCUV77Zj1FFaEajzvhgO6N3h80ZvmW1MHnGYf2TLofy3we2b8TV48dQGw5a6ccf63X9nk9nHt4LwAi0V3Xjbc1U/ApIiIiIiJxJZVhAJ67fATPXT6CvfMyW3hGjliAF5tPbM1nobue88GPlzH+oekAjBnUJf64Pp2yKCwLEok2vnvv8i2ljOjXkSUTT0w6npVQcguwdwdnTqMHOs87ol8nfn/iICaeNqTO6991+oH0aJ9B/rbyRs9td6TgU0RERERE4mJBXWtbh1gacDrO5mY4mdNQOIq1Nr6dCsC67RUA8e60r111JB2z/UQtbC9PXXr7xrz19LnxHUoD4Rrnlm8pZUDXHNJ9ycFmZrXgs3enbGbddCy/OKYf4OxnetWYAeRl1Z75jBnepyOzVxXW2723LWhdP1EiIiIiItKiYmsp69sKpbl1a+c0HDp4H6cDbjAS5aInZ6ccu600yIkHdOeQXh3o3SkLqL2E9r4pSwHYUlyZdDwStRRXhumSU3PNa2Kn25ju7TPq7eCbyuF9O7KlJMCawraf/VTwKSIiIiIicaFIFGOS9+RsDX4+qi/PXz6CcYOdNajBcJTPErKeUBUUbisL0jnXyToO7JoLUGtwV1zprBO9/qVvWZawlUsse5rhboPy9i9Hxc9lpAg+d9Z+e7UDnG1d2joFnyIiIiIiEheKWNK89e/D2dx8Xg8j+3cizd07MxSJctSAThy4d/v4mIpQhAc+WkphWZBO2U6mNLa9S1F5zWZEULXG9es1O3h3wab48VjwGSuxHZLwPNX37/wherrrRde7JcNtmYJPERERERGJC0WipLWyrGei2FrUUMQSDEdrdM994CNnm5jOuU7wmZPuw+sxzF9flPJ6iY2IfN6q110Rz3xWZTn36egEirsyMO+Y7WRot5Xt3HYwu5MG9zk2xvwbeM9a+5Yx5nFgf+Ada+3EJpudiIiIiIg0q3AkGs8utkZp3qrMZzAcJSsrdUjT2Q3qjDF0b5fBkk3FNcbMXV2YdD8YrtrypDJF8Pn6VUexfseuzVCmeT3kpvvYUUtmti1p0E+VMWY00N0NPE8HvNbakUA/Y8zAJp2hiIiIiIg0m2DE4vO05uDTyToGI1EC4Sh+n4crju5XY1z7zLT47R/t342NOyprjPlk8Zak+5WhCBPfXsTKglIqQ04gmthcqFNOOkN75u2S15EoLzstZTfe4soQny7ewtbSnduntLWp96fKGJMGPArkG2NOBcYAL7qnpwCjUjxmgjFmjjFmTkFBQfXTIiIiIiLSSoUiUfze1lt2G8t8riooY21hOek+Dzf9eD/+fd6hSeM6ZFdtc7J3XiYlgTBFFcnZxUAoSpbfy4o7f0y7DB9rt5fz2Oer+Mk/Z8TLblN1tt3V2memxdeeJlpZUMYlT81mwbrUJcO7m4b8SeNCYBHwN+Bw4GpgvXuuEOhW/QHW2knW2uHW2uFdunSpflpERERERFqpUCSKr5Xt8ZnI75YE3/H2IsqCkfj9WGOhmFgXWYAeec5azQ3VSmZDESdz6vUY0tO88QCwNBCu0e22KeWmp1FSWbPsttzde7T6vqK7q4a8k4cAk6y1m4DJwGdApnsup4HXEBERERGR3UBFMNIs2b6dlVYtMG6X4QSdA7rm1PqYvTukDj6DkWj8ehlpHkoDVdnHskDNNZ9NJTfDR3FFzcxnedBVzbKZAAAgAElEQVSZQ7a/wa16WrWGBI7LgVgR9XCgD1WltgcB+bt8ViIiIiIi0iIqQpFWnWnLTk+eW2zfz665GeTfPT7lY3rkZQDUaBYUDNt499x0nzcpOF3q7vnZHMFnu8zUmc+yYNvKfDYkhH4ceMIYcw6QhrPm801jTA/gJGBE001PRERERESaU0UwQlYrDna65mbw3GVH8MHCTfx35mqO7N+p3sd0zk7H7/XUDD7dsltw9u5cXlzV2Gf+uh1A8wR+uRm+lGs+YwFw9YB7d1Vv8GmtLQF+lnjMGDMG+BHwN2tt21j9KiIiIiIizFm9ndEDO7f0NOp05IDOjOzfiVtP3r/G+tTpvx9LerWtYjwew155GTU63obC0YTMZ/JjVm4tA5qn4VBuRholgTCRqMWbsMfqx9873XjzMv21PXS3slPrNa212621L7rrQEVEREREpA3YVOQEZ9OXbW3hmdTPGFNj/SfAPh2z6Nouo8bxnHQf5W4Z65vfbmBFQamz5tPnBHvVy2vXFpa7x5u+xU27DCcnuGB9cl5ve3mQ8UP3ajNlt2oWJCIiIiIiAHznBj83nDi4hWey66X7PHy5qpBI1PKr57/h2PumEQhH4gFs9cxnKGIByPA1feA3ZlBXOmX7uey/s7HWed6PFm1mc3GAztltI+sJCj5FRERERATYVhrgsqfnAHDhyN4tPJtdb/GmEkoqw9z17vfxYzOWb4t3kk1PEWSm+zx4PE2/5+mArjn8fHRftpYGCYSjAPHPIqONZD1BwaeIiIiIiACfLimI385ObxtbeySKbVsydWlB0vF2mc5rTVVe2xydbmNy3S1jiqt1vU3ztJ2Qre28EhERERER2Wl+X9sODWKvb3NxctOhb9Y4XW275KYDcNA+efR09wVtzv1OY+s+SyqdxkMx1ee7O2vbP2EiIiIiItIggZCTGbzuR/u28EyaRmz7mOpbmoQiTplr/y45gBMExgLV5mz0k5flrO0sLAuyvTwYP76pDQWfbS+fLiIiIiIijVZU4ZR7XnRkn5adSBPxpShfPbxvRx69cDgAZwzrSf+uOQzsmsM5k2YB0COvZtfcprKPm21ds62cHLfs2e/zcOv4/ZttDk1NwaeIiIiIiFBUEcIYyG2D6z2hZjdbgP9ecng8u5nm9XBYn45AVYnuPh2ymm1+3dztYdYUljNjubPVzZMXH8ag7rnNNoem1jZ/skREREREpFGKKkK0z0xrlu6uLSE7vWYJbW17eEbd7U726dh8wWeW34vPY3hh9tp4qW1b2d8zRms+RURERESEHeVO8NlWHdm/c/x2l9x0Zt40DmNSB9rd2zklsJ2acY9NYwztM9PYVhaIH4ttA9NWKPgUERERERGKKkLkteHg89bx+8VLb/My09irfWatY0f0c8pvezVj5hOge/sMQpGqTrdZbSzz2bZCaRERERER2Sk7yoO0a8PBp8/rIRB2Otsu21Ja59hLj+rLwfvkMdxdA9pcRg3szMINxfH7bW2/VWU+RURERET2cH//cCnfriuie7vm6+7amnk8ptkDT4Bxg7rGb0///Vg6NmPZb3NQ8CkiIiIisod7Z8FGAK4/YVALz2TPNqx3h/jt5mx21FzaVh5XRERERETilmwqYcrCTVwzbkCtzXUAMtO8jB3UJb7dh7QMn9fDTScNxttGOw4r+BQRERERaaMueuIrNhVXkpHm5cgBnTigR/uU4wLhCOm+ttXcpi4Pn3doS0+hVlcc07+lp9BkVHYrIiIiItJGBcIRAP7y7veMf+jzWscFw1HSa9nzsi25/6yD6Nc5mxOHdG/pqeyRlPkUEREREWmjsvw+tpeH6h0XCEfxe9t+8Hn6oT05/dCeLT2NPVbb/wkTEREREdkDWWspD4YbNDawh2Q+pWXpJ0xEREREpA36es2OBmU9AQKhPWvNp7QMBZ8iIiIiIm3Qwg1FANw6fr/4sRtens+mosqkcRXBCGXBCHmZac06P9nzKPgUEREREWmDbntjIQAXHdknfuyFOWv5z7QVSeMWbyoGoE/n7Gabm+yZFHyKiIiIiLQxsS63AGleDx9dd3T8fpa/qry2qDzEja8sINvv5agBnZt1jrLnUbdbEREREZHd3D8/Wca67RXcfcZQACqDUQBG9OsIwICuufGxxjhbq7yzYAPPzFzNqq1lPHHxYXTM9jf/xGWPouBTRERERGQ3d++UpQDx4DMYcYLP8UN71BhbXBHm+L9PI39bOQD/Pu9QRg1U1lOanspuRURERETamFjw6fea+LFxg7sC8P7CTfHAE+DHB+7VvJOTPZaCTxERERGR3VBxZYjJs1Zjra1xLhR2g09f1a/7j144nEHdcikoCcSPJa7/FGlqKrsVEREREdnNhCNRht4+BYBhvTvEjwfDUfw+TzzzmeatCj69HpO0rnPC0f04a3jPZpqxiDKfIiIiIiK7nXXbK+K3I9GqzGdJZQhwglAAvzf51/1fHjsgfvvmH++X1IhIpKkp8ykiIiIisptZtbUsfjuW5QQoqQzTKSc9Xlqb5ksOPo/s35lJFwzj+40lzTNRkQQKPkVEREREdjMrE4PPcHLwCXDJU7MBSPfWLHQ8/oDuHH9A9yaeoUhNKrsVEREREdnNrNpaGr+dHHyGksb165LTbHMSqY+CTxERERGR3cymosr47Quf+Cp+e9aqQsKRKGlew5Vj+tO9fUZLTE8kpTrLbo0xPmCl+wXwS+BM4MfAV9baq5t2eiIiIiIiUl1pIEz7zDSKKpIznQ99vIwOWWmEIrZGsyGRllbfT+RQ4Hlr7Rhr7RjAD4wCDge2GGOOa+L5iYiIiIhINWWBCHlZaSnPLd/ilOT6fQo+pXWp7ydyBHCyMeYrY8zjwLHAK9bZyfYDYHRTT1BERERERJKVBcLsnZeZ8tyOcicbmq7gU1qZ+rrdzgaOs9ZuNMY8DWQCS9xzhUC3VA8yxkwAJgD06tVrF01VRERERETAKbvt1TGLxy86jE8Wb8Hv8zC0Z3vOemQmOyqCgDKf0vrUF3zOt9YG3NtzgDScABQgh1oyp9baScAkgOHDh9tUY0REREREpPEC4QhbSgJkp/vI9HsZP3Sv+LmcdB9bip1f37XmU1qb+n4inzHGHGSM8QKnAdk4az4BDgLym3BuIiIiIiJSzX1TlgKwYH1RjXPZfh/L3DWfW0sDNc6LtKT6Mp93AM8BBngTmAhMN8Y8CJzofomIiIiISDOYtXIbkz5zNqJI3N8zJtPvjd8+74jezTYvkYaoM/i01n6H0/E2zu1wOx540Fq7qgnnJiIiIiIiCW5+dUH8dt/O2TXOZ6c7wedB++TRIdvfbPMSaYhGF4JbayustS9ba1fWP1pERERERHaVfl1yAGdt559OPaDG+cw0J7c0qFtOs85LpCHqK7sVEREREZFWokuunw5ZaXxz2/Epz1eGIwDs2y23Oacl0iBqgSUiIiIispsoqQyTl1V7Oe267RWAgk9pnRR8ioiIiIjsBjbsqKA0ECa9rv07rbPL4YCuKruV1kdltyIiIiIirVg4EuXyp+fw6ZICAIb2bF/r2IfOPYSPv9/CXu0zmmt6Ig2m4FNEREREpBWbsmhzPPAE8HlMrWN7d8rm0lF9m2NaIo2mslsRERERkVbsqme/Trrv8+pXeNk9KfMpIiIiItIKlQfDGGpmOdcWlrfAbER+OAWfIiIiIiKt0KF//pAOWX7SfR4C4Wj8+MaiyhaclcjOU/ApIiIiItLKhCJRKkNRBZrSpqhgXERERESklVmyqaTGsRtPGtwCMxHZdRR8ioiIiIi0MgvWF9U49otj+rfATER2HQWfIiIiIiKtzLrtyU2F3rj6qPjtXh2zmns6IruE1nyKiIiIiLQym4oCSfeH9mwPwBc3jiMnQ7/Cy+5JP7kiIiIiIq1MWSCcdN8YZ8uVHnmZLTEdkV1CZbciIiIiIq1MZTjS0lMQ2eUUfIqIiIiItDKVoarg0+/Tr+zSNugnWURERESklQmEo3TM9gOQ5fe28GxEdg0FnyIiIiIirUxlKEr7zDQActLVpkXaBgWfIiIiIiKtRDRqmTxrNd9vLMbvdX5VP++I3i08K5FdQ39GERERERFpJd79biO3vv4dABl+Lwv/dILKbqXNUPApIiIiItIKfLpkC69+vT5+/9Kj+pCtkltpQ/TTLLKTrLUEAgECgQDW2paejojUwePxkJGRgd/vb+mpSCu1amsZ//0inz+cvD9ej2np6cge6pInZyfdz0xTxlPaFgWfIo1UWFjIN9/MZuHCaZSWbiQjw+DRLyoirVokYqmosHTrti8HHDCaQw4ZRmamNmqXKtc89zULNxRz7uG9GNQ9t6WnIwJAll+/qkvbop9okUbYuHEjkyffxUEHlXDmmR3Za69eGKPAU2R3EIlEyc/fyLx5k5g3byAXXXQd2dnZLT0taSXKg86eihbLluJKlm4uZdTAzi08K9nTHNCjHau2lsV/HrW/p7Q1+okWaaDS0lImT76bU06JcvzxvenRI1eBp8huxOv10L9/R844ox/77ZfP5MkPqWRe4kKRKABlgTCn/msG5z/+ZQvPSPZE4Yjl6IFdmHjaEAB6dlCFhrQtCj5FGmjhwu8YOLCYwYP1l3CR3d2YMT0JhZayYcOGlp6KNJNtpYE6zxeVhwAoqQyzsagSgGA42uTzEkkUikRJ83k4f0Rvlk48iR55Cj6lbVHwKdJAixZ9zv7757T0NERkFzDGsP/+hoULv2npqUgz+GxpAcMmfsS0pQUAVAQjPDZ9JeFIVXBZEggDUBmKVB2rDDXvRGWPF4xESXP7SKjkVtoi/VSLNNCWLfn07NmupachIrtIz57ZFBSsaulpSDNYvqUUgIue+IqX567jjrcXMfGd7+PBaFFFVZAZilSVYh959yfNO1HZ44UiUdK8+vVc2i41HBJpoECgAr+/Y0tPI66iIoTP5yFNbdj3KKWlQbKy0tRheRdIT/cSCJS39DSkGXRtlx6/ff1L39K9XQZQtY3Fss0l8fOhhGxoQGW30szCEUuaT/9/l7ZLf1oRaTDLruov9Nlnq/nHP2o2szjrrJeYMmVFrY877rinWbhwCwCTJ8/nxBOfrfN5LrnkDV5+eVH8/h//+Ck33/xxvfP705+mMnny/HrHieP226fy+uuLGzw+lFDW1xADBjxEWVkQgLvums7ll79Z5/jjjnuar75K2KT80jf4z3/m1Ps8l132JlOn5jdqbrszYwzWKrjYE3ir/c97U7GzpvObtTt4eOoKtpYG4+fCkeQmVKVuOa5IU4tGLdvKgkSiaoQmbZeCT5FdZMaMNXTu/DfGjHmKMWOeok+fBxg06J/x+3l5d7NokVPidcABXfjHP77if//7Lukafr8Xvz85k1lSEmDGjDUAZGT4SE93ChZefXUxV145vM45XXjhUJ59dgHg/KP2zDPzueSSg2uM+/nP3+Doo5+Mz/Xpp+fzu999GL8/evST/PSnL+zcGwPMnr2eU0/9HyecMJn33lsGwF//+jndu98b/8rJuZM77pgGwB13TKNnz/vp2fN+nnyy/jV5V1zxFj163Ef//g/xzjtLk86tWrWdXr3+TpHbQOSVVxax9973M3PmWgBeeOG7GtdrjLlzN/C3v81g0KBONc6FQhGCweRAMxiMMGjQP1m+vBCAI498nLlzaza92bKljK+/3ggkf+6vvbaYK688rM45nXfegTz/vPO5FxcHeP/95Zx99gE1xo0f/xzHHPNU/HN+773lXHLJG0mf+5VXvt2Ad6F2Eyd+xu23T43fr+tzr80HHyznpJOe5ZRTnk8KqlN97g88MIt+/R5kxQrn/f2hn6+0DaFafpm/54Ml/PX9xUlrO0PR5D9IbHL/3yHS1Oau2Q7Auws2tfBMRJqOym5FdpHqQWNdYzp1yuLll8/iN7/5gLPPPqDOLVvWrSvmd7/7kC+++Hn8WH7+Dj75ZBWbN5dy992fU1YWwhiYMGEY1147gv79HyInx4/PbVYwfPgkwuEoRUUBzj33FSIRS2lpkO++u5L0dB+33HI0WVlpdO+ew9Kl27jssjf58MMLiEYtmZlpLFy4Be9OrkEpKqrkvPNe5ZFHTsYYw1lnvcSSJddwww2juOGGUfFxo0Y9wamnDuK777YwbdpqVq++lg0bShg2bBI//vFAunVL3ezpnXeWUlERZsOG3zJ//maOPfZpNm78bfy1/+pX73PTTaNo394ps3vmmfk888xPefHFhQwc2InoD/gLc0lJgAsueI3+/Tty5ZXvAPD552sYNaoX4ASa48b1ZeLEcfHHPPHENwwf3oMBA5wSbr/fG39vlyzZyoIFWzjzzP2ZO3cDzzwzn+eeOyP+2M8+W83Kldv5xS+cgLC8PIS18Oc/j2XEiJ6MHftfsrLS8HoNHo9h+PBJVFSEiUYtP/rRM4RCUbKy0pg50/lZ+utfj6N37/bk5qbz6aer+Oc/Z/P882fg8Rh8Pg8zZ66ld++8nX5/Hn10LnfeOZ3f//6o+LHaPvfarFy5nV//+n2effZ0Vq8u4vTTX2Dt2t/w7rvLUn7ub7yxhHvu+RFvv72UceP60rWr9vEUkhoLpbKlpKoT7hcrtiWd21RUyYCuajYnTW+r+3N4508PbOGZiDSdBgWfxphuwPvW2kOMMY8D+wPvWGsnNunsRHYj1sKoUb14/fVzAKcUs2fPdlx22aEAjBnzVNKegkOHduOjjy6od6/QtLSa2dC//W0Gt912NLfccjTRqKV//4dYterX8fMrVvwKcIKTTz9dxfjx+wLw3nvLOPbYfjWuN2PGGu67byavvno21177PnfeeSyTJs3l88/XMnHiWM4662VuvXX0Tm0zs3FjKRMnjmPs2L4A7LNPe9atK6ZDwt5ln3yyii5dsjnooO689NJChg/fC6/Xwz77tKd37zw2bSqtNfhctKiAkSN7As57ClBWFqR9+wzefHMJq1ZtZ8KEYfHxxcUBevVqT3FxgFdf/Z4LLhja6NcEEAiEOeusl+naNZsPP7wgvvY2L+9upk69OOVjtm+v4Pbbp/Kvf/24xrmSkgBnn/0yF110EJD6c7/77s95/PGfcN55Q1mzpojzznuV6dMviZ9ftuyXAGzdWs6CBZsZO7YvkUiUDz5YwYknDqixTvTNN5fwwQcrePrp07j99mk88sjJ3HTTR3i9Hs48c38uuOA1Jk06hR49chv9/pSVBXn//RX88peH1zom8XOvzebNpfzjHycxbFgPhg3rwYQJb1FaGqz1c7fW0qFDJosWFfDpp/n86ldHNHru0vaE6/kjU0FC8PnOfKfi4Ii+HflyVSEbiyqadG4iMZvdcvAR/VpPfwmRXa2hmc97gUxjzOmA11o70hjzhDFmoLV2WRPOT2S3kZnpY8eOSsaMeYpFiwoIh6MMHdqNyZPns2TJNgYN6kRampcHHpjFY499TWFhBU88cSp/+ct0ysudzOWqVTuYPXsDubl+AoEIt9wymuHDeyQ9z+LFW/n441V4PIZzzz0Qv9+bMjjIz9/BWWe9RG5uOkcf3Zto1PL3v8/i5z9/k6uuOoxf/GI4nTtnAXDBBQex776dmD59NRs2lPDb306hS5csXnjhTBYv3sqkSSdz1FG9dup9GTy4M4MHdyYSifL664sJhSLsv3+XpDEPPDCL3/52JAD779+F226byrXXjmD58kK2bi1nv/26pLo0AEOGdOWuuz7nnHOG8OGHK+nbN4/27TMIhSL85jcfkJeXwRlnvMi55w7h7LOHkJeXwfLlheTmphMKRcjMTNup17V1azlDhnRh4MBOHHPMU/FAsbQ0yDHHPEU4HKWsLMibb55Lr17tiUYtl132FsFgpEYWuaCgjAkT3uKiiw7iN78ZmfL5PvlkFTt2VHLddVM444z9WbOmiF692tcY9+23m/jZz15i2LAeHH10b9auLeaOO6bxy1++x69/fQSXXnoIOTl+AG6+eTRjx/Zh8uT5BIMRzjnnZQ45ZC8effQUPvlkFW+//X87va9tdrafV145K6nktrrEz702I0fuAzglzP/5zxyGDetBbm56rZ+7x2MoKCjD4zG0S2gyI3u26us4q0tVWtu/aw5frirkdy/P52fD92mqqYnEbSoOkOY1dMjyt/RURJpMvXV0xphxQBmwCRgDvOiemgKMquVhInucAw/sxhVXDCM7209Ojp/rrz+S8eMH4vN5OO64fjz33Bn06ZPHtdeO4LvvruL44/vj8RimT7+EuXMnMGfOBE46aQCPPHIyc+ZMYMGCKznnnCE1nic318+TT57KKafsy7Rp+XzzzUYOPbQqcxQIhLnnnhkcffSTXHXVYXz88YXk5qbTvn0GU6ZcwAcfnM9XX61PWsNZUhLghRcWMmhQZ669dgQHH9yNSZNOYezY/1JZGebGGz9mwYLNSfN4+OHZPPjgrAa/Pw8++CXnn/8aV1wxLCn4WreumJUrt3PMMX0AJ/jcZ592jB//HJde+ibXXz+yzpLmceP6sn17JT/+8XNcf/0U/vCHowF46aVFbN5cytVXH8aZZ+7PNde8x/vvL+fSSw/h6qvfpUOHDCoqwgwe/E/y83c0+HXE7L13O+6553iiUcvxx/dn6tSLmTr1YnJy/EybdjEzZlzKvHm/iAeIL7+8iFAowrnn1vxML7rodX71qyNqDTwBevTI5ZFHTuaYY3ozc+baGp97cXGAm276iNNOe4G///0Enn/+DLxeD3365DFr1mX897+n8dJLi+Ilu+CsK/3Pf+Zy/vlDOe20QYwfP5AbbjiKceP+SzAY4brrPmDNmqKkedx553SefvrbRr9f1VX/3Otzww0f8dvfTolnUmv73M8++wBuv30aoVCUDRtKOPTQRyguDtR1aWnjiitDvDFvfZ1jvt9UXOPY70+oKgdPrFoRaSqbiyvpmpuhbubSptUZfBpj/MAfgBvdQ9lA7P/ghUC3Wh43wRgzxxgzp6CgYFfNVaTVy8nxc9FFB/GjH/Xj/feXk53t59lnT6e0NJjUKCWmIf/ABIMRAoEIn3++hvXrS9h773YceeQ+/PSng3n++e94551lHHdcv/h4n89DUVGAvfbK5Z///IrhwyclfV1yyRukp/v48MMLAIhEoowe/SSDB3dm2bJt3HffTObN28zFF79O374deO21xdxzz4947LGvk+b1wgsLeeaZhnfEve66kSxb9kvuvPPzeLMdgOeeW8BZZ1U1w3nqqXn07ZvH119fwZIl1/D660uYPbv2XxzvvHM6//d/Q5g58+csWXINf/zjVNavL+bLL9dx+eWHcumlh3D++UO55prDeOutJZx88r6sWPEr8vIymDFjLddffyRvvbWkwa+juob+knDWWQfw8stnxcusw+Eod9/9OTNnrmPSpFM4//zk8t9gMEJpaTCe8Rw8uDMHHtit1s/d63Wum57u5Y9/nFrjc7/22vc55JDuPP74TwDnDw4jRz7OGWfsx+TJ83n11cW8/voS/vCHT8nMTCM/fwdXXjm8RqA5adJc3nxz59+vmOqfe33uv/8E5s6dwKWXvkFJSaDWz/2KK4bz/fdX06lTJh99tJJzzx3CtGn5P3i+svv6+4dL+XJVYcpzZ7sZzdXbyuPbr8TkZfkZPdDJ/Mf2/iwsC9Lnxnd4cc7aJpyx7Kk2F1fSvX1G/QNFdmP1ld3eCPzbWrvD/YWpFIgt1MqhluDVWjsJmAQwfPhw/blQ9ghPPPENkyfPZ9asdaSleRk0qBOPPvo1Tz/9LT6fhzvumMbLLy9i8uTTkx737LPz+b//O7DWtZ9z5mxg7doiXnjhu6TmOCNH7sPatcWsWLGdhx46KX7c6/UwceI4XnttMd9++wuuvfZ9zj9/KDt2VPL552u49dajOeKIx8jIcP7ztxY+/fSi+BrMCy44iFtv/YTu3XO44opheDwGr9fDsGF7EQ5H4418alvXWN3y5YWUl4cYOrQbPXu247DDerBkydZ4w51XXvmeRx89JT5+1qx18bJcj8dw8MHdmDNnA4cdtnfK68+atZ6rrnK6/mZmptG/f0fmz99Mu3bpdOxYta40I8NHXp7zj/qKFYUMGNCRN95YQt++eXzxReN/kbzjjmm88cYSystDRCLR+BYlpaVBxox5CnA6DJeWBrnnnh8lrbUtKChjyJB/M3ZsHw4+uDs9e7arcf05czYwf/5mPvhgedLx004bzHXXTaFnz3ZJayWzs/3cdddxvPrqYubMmcDJJz/HY4/9hNdfX4zP52HUqF7ccMNH8a65GRk+5s6dQF5eBj/5ySBuueVozj//Vc45ZwjHHdcv/vNxwgkDiESi8Wx1fv61jX6vUqn+uddm3rxN5Ob66d+/Iwce2I0ePXJZs6ao1s99773b8emnqxgzpg+vvrqYTp2y2LFD3Ur3ZCWVNbdKueKYfkwY3Y/2mWm8NHctUQu9OmbFt2CJOWbfLkxftpXKcAS/z0P+tjIAnv1yDWepFFd2sU3FlQzu3vg19iK7k/qCz+OAccaYq4GDgV7AWmAWcBDww//8LdJGHHroXnTrls277y7jmmsO57XXFpOVlcbpp+/Ht99uYvz4fVm9Orm888EHv6S0NMjpp+9X69rD8847kPPOOxCv18PJJz8XP75mTRHBYISMDB/l5aEapal19TFKPPfOO0u5++4ZpKdXPX7Vqh34/d6kPUIjEcvVVx8WLwV++OHZBIMRfv3rEXW+Lxs2lHDFFW8zc+bPqagIMXv2Bv797/EAbNtWzqpV2+MNYwD69u3ACy8sZMyYPmzfXsnzz3/H88+fUdvl6ds3jyefnMfAgZ1YsaKQjz5ayd/+dhw+n4fbb5/GhAnDCAQiTJ68gPvuOx6A995bzlVXHcakSV+zbl1xfG3ggw/O4uGH5/DWW+cycGDNrVMS3XbbMdx22zE1jtfVcCimS5ds3nvvPPr27RAPVGPmzdvEAQd04cYbR3ctl4wAACAASURBVMWv/847VUvrly7dRiQSJSfHTzAY2enP/fHHv+Hpp79Nevz332/l2283c++9X8SPhcNR/vKXcfHy2DvvnE7Pnu248MKD6nyNdUn1uddm/vzNPPnkPN577zxWrChk06ZSBg7sVOvnHnvMr389AmOcbsv9+nXY6bnK7i8Yrtnp9vwjetMpx/nvPjcjjaKKEIf0yqMyHGG/7u24bLTTIC3dbSQ24ek5XDVmADkZ2iRAmkZBSYCVBWUcs2/tPQ5E2oI6/y9qrT06dtsYMxX4CTDdGNMDOAmo+7dOkT1IMBjh7rtn0KtXezp0yMTrNRjjHH/yyXnccssn3HHHWPr2dX4RXrOmCGvhnXf+r86mN4nrI2PLjj74YDkTJrzN9dePJCfHz4gRj3HzzaP52c/2b3QDnVNPHcyppw5OOhbLfF5zTe2dSl94YSGlpcF6g8+jj+7NhRcOZb/9/kV2dhoPPHBCvEHSZ5+t5vDDkzOaV199GHPnbuToo58iLc3DlVcOZ/To3qxdW8T48c8xf/6VSeNvu+0YLr74dQ4//FHatUvnrruOpW/fDvTt24F58zYxZMjDFBcHmDDhUI4/vj+RSJR27dLxeAznnHMAN974MR995JQgFxSUs2TJNgKB5L05GyMatUSjttZy3GjUYq2N/xx4PIZ164o5+ODuBAJhTjvtf0yadArHH98//hhrncc9//wCfvObD3j44fF8990WjjzycW65ZTSnnDIonpFuqF/8Yji/+EXyPrGxzOfJJ+9b6+MmTZrL8OE9flDwmepzr+3zveCCocyevZ7evR+gS5cs/ve/M/H7vbV+7tu3V8S3hznxxAFMmvQ1M2ZcutNzld1fKGGblfevHc2niwvomdBtOzPNS1FFiHaZabx5TXIriwz3v6tZKwvJ3zqff5/vdC/XijzZlT5ZvJlLn5oDQLd2KruVts00dhG9MaYD8CPgM2ttvbvgDh8+3M6ZM2cnpyfSetxxx6XcckvP/2fvvsObLNcHjn+Ttkn3opTSAZRZ2rL3RraigAMERQXBhfI7RwHRAx5QVETFjXoQBURRtiDI3hvKaKG0QIEuSlu6d+b7+yNN2tC96OD5XJeXzbvyJECa+33u576L7XcpSRKvvLKdp58OYOjQlqxfH8orr2xn06YJDBliuIN+7Fg0oaGJvPKK4Qv/9u3XGDy4hanyKMCECRuYNq0LI0e2LnYMw4evYeDAZqxYcYGVK8earn3w4C3mzNnLl1+O5PDhKFauvEhKSi5NmtiRlpaHra0VkmQoRuToqCQxMRsnJ2smTgxg8eJhRZ5n7ty9eHjYl1oAp6EaNuxXNm9+utKVUpXKD0lPf8eUtnqvl17axrBhLXn6acMM8rJlZ1i27Cx6vYRMJqN9ezfWrx9vFky2afMtL7zQiT//vMxvvz1B586GdNuNG6/w4YdHWLfuKb788hT79t0kOdnw556cnGsqqiSTGfqJpqersLOz4u23+zFjRo8iY3v66Y1MnBjA44+3r9Rrr2+io9PZu9edadPere2hCDVo+uqzRCXn8MuUHvi42hbZ/9i3x7h0O535o9szfUBLs31/B8cx848LAAR6OfL+mECe/OEEnX2c+ev1fkWuJQiV8cba82zPb/Gz7JmujO7YtJZHJAiVUq77chUOPitKBJ9CQ1Fa8HmvvDwter2ErW3l2niUpbh0S6Hqzp2LIzg4gRdf7FLbQymWRqMz9RMVqk4Enw+G534+TWaetsRg8fW159kRcodF4wJ5rndzs317ryTw0q+G7zD9W7vx5vC2PPnDCbo0c2bLDBF8CtVj+uqz7AtLBGDPmwNp20Ss+xTqpXIFn2LxgiDUgJJmvaqLCDxrRrdunnTr5ln2gbVEBJ6CUHFZKi1WFiV/J2qWPxualFm0JY+1lbzQzxaA+Q37hIw8YlNz6NbctXoGKzyQslSGolijOzaljbt9LY9GEGpWxRYJCYIgCIIg1BN5Gh0XotM4G5la4jE9WhjWX7sUk6liXeiGT0q2irQcDQAXotPQ6yUe/fYYT/5wsppHLTxoTt1MoaevK8ue6Vpi5XtBaChE8CkIddz168nExhZtgF5ZMTHpDBmy2vT4scf+ICPDcMf/+PFopkz5q9qeSxAEoTYlZ6vLPGaIXxPWv9KH5/q0KLLP2rIg+Dwfnca01QXLiC7dTudu/mypTi+6ygmVk5lnvKFR8g0SQWhIRNqtINwHM2f+w6FDUTRqZGO2PT4+i7Fj27FkyfASz1227CzW1pZ88knRwkAATzyxjpCQBLPCRYWlpOQyfrw/S5eOBAwpu1ZWFuh0etRqHcOG+RISkkDnzh5cvZpM06ZVS/lp334Zqam5AFhayomNfQuAH38MYuHCQ3h7O7Jhw3hTtdfijB37J6dPx5q9hn37nmfr1nB2777B0aNTcXKyZvPmMJ56yr9K4xUEoeFKziqaSlucnr7Fp80WTru915lbKaafs/K0ONXQGn+hYctRG6qr31vsShAaKhF8CsJ9oFRaEhDQmNatzb/ghIQklLmOT6m0wMur5OIDVlYWrFgxhsGDWxS7f9Wqi4SHJwGGno06nYRMZqi++8ILf5Gamoe3tyNubrZ06OBOcnIun356nFatXHjyyYoFdjk5GmQyiI+fbbb90qUEFi06wvnzrxAVlcYbb+xkx45nSrzO1q0TTT+npOTSp8/P9OzpxXvvHWTatC4cORKFpaWcLl08KjQ+QRAeLLH5N8L+fLlyneGsSikw99E/YaafM/I0IvgUKkWlMbQCat1YrPUUHgwi+BSE+0Cr1RMWlkR8fJbZ9sTEbPz9zRtKp6fnYW+vMFXV1Wr1Zr07VSotOTkanJyskctlWOXfmb94MZ7p07eZXevo0akAprYdBw/e4j//OUBERArHj8fwxhs98fFxJC9PS6dOHjz77GZmzOjOF1+c4qefHqvw6wwOjqdDhyZFtv/1VzjPP98RT08HPD0dSErKITtbjZ1d8bO1hX311SlmzOiOtbUlMhk4OVmTkaEiJSWX0aNL7kcpCMKD7dj1JI5FJGEpl9HZx7lS13AqZ99kY8EYQagoldYw86ksZZZdEBoSEXwKQg3S6yU0Gh1ffTWqxGMkSUKl0qJUGv45Bgb+kN/z0bA/NTUPKys5CxceMl1TpdJx6dJreHoWzIhqNDr8/Nz47bcnAGjR4iuzXpEAw4e3okuXpkyevJlnnunASy/9Tb9+PshkcOBAJMnJObz+ek/WrAkx9RCtiAsX4jl2LBpPz6XY2Fjx5ZcjGTOmHbGxGWYzs56eDkRFpRcJvO+lVuv4/fdLBAe/anrtKSm5WFjIaNfOrcLjEwThwZCeq2Hyz6cB8G/qaFY4qCJc7BSEfTCKORuDTX0Yi2NMnRSEilJpDTOfinK0cROEhkAEn4JQgyIiUnj++S2Eht6lU6cmaLV6rl5NJiCgIOiSJMNs5sGDL+DgoCQm5k2zawwd+ivNmjmxcuXYUp+ruAp5xW27cSOFI0ei+P33EJKTc9i+/RqSBM2bO6HR6Cmu9+8PP5xFrdbxr3+Vnrpmb69gyZJhTJ7ckVOnYhk79k9GjmyFTifh6Kg0HWdnZ0VaWl6p1wLYtOkKI0a0NK1nHTSoOX/+eZnHH/fj4MFbLF16kj17Jper96ogCPVHnkbH1fhMOlVyxjIho+DzpYOXU5XGYqOwQGFZ+mdMjlrMfAqVUzDzKVppCQ8G8Y1NEGpQ27aNOHVqOp6eDkycGMjjj/vRq5cXjzzShgEDmjFxYiAtWjhz5sxLODgoi5wfG5tBZGQaQUFxREenl/pceXla/vnnOp07/0jnzj8SF5eJ6p5UsI0brzB9+t/07u3NjBk90Gr1vPNOf3r29GT48JZMn96FkydjadTI1uy8detCWbMmpMzX+/zznZg8uSMAvXt707y5E8HBCbi4WJsFm7m5WuTyssvJr1kTwqRJHUyPFy0awtGjU3F3t+Ps2Tj8/d24cuVumdcRBKF++Wz3VcYuO86Nu1llH1yIRqdn47lYopJzTNsCvByrPJ6yZqWyVWLmU6g4nV4iM8/we1pZxg0OQWgoxN90QbgPsrPVbNx4hW3brgHw+ON+ZGWpGTiwOUCJgdhbb+3m9dd78N//DuTll/8u9Tn6929GSspcLl58lYsXX0Wtfq/Imspx4/zYt+85FAoLZDIZMpkMS0s5FhZyZDIZffr4sGTJcQIDzdNhDx2aQlDQy2W+zl9/DUZdKP3s9u1M5HIZ3bt7cvKkoXqtJEmcP3+n1CJKYFj7GhycQL9+Pmbbt2wJ5/HH2yOTyXBxsSnXDKogCPXL7fxCQaFxFWszdTYyhdkbgnnp14KWKB6O1lUeT0mFh76e2BkQM59CxS3YeplW//mHKSvPAlQ6NVwQ6hsRfArCfeDhYc/mzU+zYMEgrl9PITExm8TEHF59dTtz5/Yr9pzly88RHZ3OzJk9GT8+AEdHJe++u6/IccVkyRZzjOEgY6BpdOtWKh9+eITt2w1B8fDhLdmz5wYjR7Y2O/+HH87y9denynyeI0eiWLr0BDk5GpYtO4NCYUGHDu48/HAbtmwJZ/PmMBYtOkKjRjb4+JSeCrd//y369PEuklKblJSDm5thZjYjQ2WWzisIQsNgqzR8Ed8RElehYj7HrieZPe7RwoWBbUtfW14exQWfkZ+Mpk+rRgBkizWfQgVodHrWnok22+bnUfoNWUFoKETwKQg1SKfTM2rUb8TGZjBt2jaOHInC3d2Obt08adLEDkmCn38+T1RUmumctLQ8Xn99B599doKNGyeYWrH88stY9u69yaRJm0hMzDYdr9HomDFjB927Ly/2v/ffP4w2v6ABQG6uxjTT2rOnF0FBL5sC4C1bwnFyUvLDD0FmKbvlTbv9+OOh7Np1gyZNPmf9+its2zYRpdISR0clGzeO54svTnL4cBS//24oinTiRAyjR68t9lqHD0fSu7e32bYrV+7Sq5cXAAEBjTl9+jYBAe5ljksQhPrFmOa6OzSBR74+Wu7zvj90w+zxhlf7VsuMkqez+ezph+MCAbBTGEpn5Ihqt0IFRKfkoNFJPNbJEwA3e4WY+RQeGKLgkCDUIAsLOcuXP4aPjyMymYzY2AyOHYvm44+P0rq1K9988zBr115i/vyDrF49jsOHI3niifWMGNGK06en4+pqY7qWvb2CffueZ/r0bXTs+ANXrryOq6sNPj6OLFw4uMTKsdu2XeX69WTAkMrq57eMd97pR17+OpMrV+7y3/8e4oUXOrFzZwQhIa8xd+4+vv/+LG++2QcwpN2Wh7u7HYcPF39snz4+HDv2otm2vn19Suz3+fXXDxfZVvg1fvfdI+UakyAI9Ydaq0er12NpUbAUITolB51ewqIc68RryphOnny4o6Cv5+TehiUTNvkBg5j5rL8y8jRk5WnxdLYp++BKiEvLZXtIHJ28nenV0jBTnp6rAQyVmP8OjuPZXs1r5LkFoS4Swacg1LBmzQrSS729HYsEcs8804FnnjEU1Rk0qAXbtk1kwIDifxE5O1uzceMELl9ONAWmS5eOLPX5x4xpZ/rZycmaxMTZprWg+/Y9D0Bi4mz0eol58wbg4mLDzz+PQafTF3s9QRCEmjL6m6PcTsvl6R7ma71DYtPo0sylQtca38277IPKyd3Rmv8b2oZv9l832y6Xy7BVWJAr1nzWG9HJOaTnamjlbseRa0m8+ts5wJBGXVF30nP55dgtZo1oV+zMZbZKS99PDgDg62bHwdmDAUxFhnr6urDj//rj37TqRbEEob4Qwacg1CFyuazEwLOwwMDKp5reW4QIDC1ZLCwMBXyM45DLRQqQIAj3T1KWiuuJhuq2t5KyzfYdj0iqcPCptKrelUVT+7YoEnwC2CosxcxnPTLu++OkZKt5ONCD6JScsk/Il5CRh7uD0qyF2az1wZy4kcyd9Dy+e6ar2fEXY9KY8L+TAHg523ArKZv0HA1OtlZk5Qef9kor2om1nsIDRqz5FIRatHDhIRYuPFTmcYcORTJ48Kpqe97DhyMZNuxXs22JidlMnbqVQYNW8cUXJ0s9f+3aS3h4fG76z8npE158cSsA8+cfoHnzr2jT5ls2bw4r9TolWbXqIlOm/FWpc2tSce9bSf76K5xmzb6kfftlnD9vaE6/ZMkxs/fN3v5jPvjgcE0OWRDqjU3nYk0/H7pq3kIpIUNVrms0dbLGLb8vsKtt0RttVVFSMGuntKj1NZ+rT0SydM9V9PpyVKB7gGl1elKy1QDsvBxfrmrKGp2eDUEx9Pp4P9/sjwAMvTkX7wzjxA3DkpbtIXeISMw0O++lX4NQa/XMHtGWryd2xkIuY/bGYADScg1jcLAWc0DCg0cEn4LwgDlz5jbPPLPZrAgRwLPPbqZXLy9+/HE0q1cHs3t3RInXeOaZDsTHzzb9N3p0G8aN82P79mucOBFDePjr7NkzmTfe+IfIyLQSr1PdyhPIV1ZJ71txEhOzmT59Gzt3Psv27ZNMbXLmzu1v9r517uzB2LHtyriaIDwY7g04C0vNUZfrGjlqHQ8HNuX36b14fUjrsk+oAGtLQzaIMbg1srGyqNWZz8ikbBZsC+XbAxEci0gq+4QH2J4rCUW2DWjjBlBs4B4ck0abeTuZs9FQcO/LfdeITMqm3fxd/O/wTQDmj26PrcKCORtD0OklMvI0LNwWyt1Mww2TN4a0oXsLV6b0bcHhq3c5dj2JlccjsbGyoEk1tAEShPpGBJ+C8ID54YcgFi16yGxbXp6WESNa8uqr3WnfvjHDhvly7Vpyua53/Xoy164lM2ZMO9atC2XatC7Y2Fjh6+tCt26eBAXF1cTLKNb779fcLGJx71tJdu+OYPjwVgQEuNOqlSvNmjkVeT8PHLhF48Z2dOrkURPDFYR6Jy2/CEtx0kvZZ6TV6UnP1eBip6BfazeUltW7dEAul/HNpC789bp5eyw7pWWN9fmMSMzi892lz2heSyiYcbtxN6tGxtFQzNtyCYDfpvXit2m9mDOyHb3ziwCpCleFV+vIVev49kDBTdhp/X0BePTbY6Ztrw5qxfQBLZkxuBUXotNo9Z9/6LhwD6tORAJgVahw1oA2bqh1eib/fJqIxCzeGNK6VotoCUJtEcGnINSwBQsO4uX1Bc2afcmaNcGlHrtq1UUGD15Ft27L8fRcyvLl58z2z5q1Gze3Txk4cCW5+V/GfvwxiGbNvsTL6wuWLDlmdvznn5/go4+OmG375ZcxtGxpvnbK2tqSOXMMX6iCg+PZvv06jzzSplyv79tvzzBzZk/T46QkwxoanU5PWNhdU0/Oirp9O5M+fX7G03MpK1deMG3/55/r+Pl9R5Mmn5tmOufO3YuHx+cAeHh8TkDA96bjS3t/KqK4960ksbEZdOxYsC63eXMnIiJSzI756qtT/PvfvSo9HkFoaDJyNSgti34tkcvKN/NpDF4bFbOuvbqM6eSJt4v5Z5qtwoJsVfXPfOr1EsO+OMx3ByMIji05g+TG3YL1sd/sv27q69wQqbV6dFVILW7qZIPSUk6/1o3o38aN1x9qjZ3CcJPC2E/2bGQK7f+7i6mrznAnPReFpZyrH47ivUf9GRnQhCyVlvHdvIn8ZDTvPOwHwIgAD5o3Kvq77tjcIaafB7RpzEsDfE2PXxnYstKvQxDqMxF8CkINio5O5+jRaK5de4NTp6YzZ87eMs+5eDGeLVue5syZl5g37wDR0ekAnDwZi6+vC3fuzCIjQ8WuXRHk5WlZsyaEU6emc/36TD7//CRZWQVf0mbP7su8eQPNrl+4WMK9jh6NYujQX+nc2aNcgVZurobt268xYUIAAJMmBfLBB0f46KMjjB69lpwcDf37NyvzOsU5dSqWP/54kpMnpzFnzl7i4jK5ezebmTN3smfPc0REzGTDhitcuHCHJUuGEx8/G4D4+NmEhs4AKPP9WbfuMgsWHCzXeEp73+6l00k4OipNj+3sFKSl5Zkex8ZmcPNmKoMGtSj3NQWhocvI09DT19X02PhPzs1eSWp22TOfxrV8LjUYfBbHTlEzM593Mgo+M67GF8xuRiRmMvLLI4TGGX433LibhbuD4fMmNUfD2xvL7slcH2l1eoZ+cYg5G0u/iVuSPI2OawmZTOvva/Z53trdUPDnX39eIDw+g/E/GmoenLqZQmhcBq8OamWaRZ87yo/RHZoyb3R7s2u3beLA4TkP8fXEzjzRxYujbz9E6PsjzdJqLeQy5o32p6mTNTZWFlhaiK/gwoNJ/M0XhBrUrJkTX301iqVLT/Lss5tJSMgu85whQ3xp1swJb29HevXyMhWradLEjtdf74GVlQWdOnmQnq7C2tqSX38dx5o1wUyYsIGUlFzTzGNlDBjQnNjYt0hOzmH16rJ/wf/99zUGD26BjY0VAI880oaNG8eTkaHi7Nk4Zs3qg2UxMxnlMWxYS1q0cKZ5c2d69vQiKCiOU6diuX07g549f6JNm2+Ji8skNLTkdWJlvT87d0awbNnZSo2vNC4u1mbBZm6uBnmh9Kq1ay+ZAnZBEAyzfFkqLZ5OBb0WFflfzt3sleVKuzUGnzU581kcW2XNzHym5xS85lvJBb87jl5P4mpCJhuCYolKzubv4DhaNrYz7d9QqHBTQ7Llwm1iUnLZfP421xMyORuZUmrQL0kSq47fIiQ2jdM3k1l2MAKtXqKjt5PZcf3buDG6Y1NO3Ehm1FdHAXjnYT/TLLx/04JqtC0b27Ps2a44l1DMamxnL754ujM+rrbYKYsvJrTvrUGcmTe0Qq9dEBoSEXwKQg06ejSKxx9fR8uWLqxaNbZc5xTOmNLrJVPQ4uvrYrpba7xpe+NGCgMHrsLV1YalS0fg41O5XmHp6Xns22conmBtbcmjj7YlNDSxzPM2bQpj3Dg/s20PPeTL5Mkdsba25LXXelRqPFDwGsGw1kqvl5Akw/WNBXtiY9/kySfbl3iNst6fVavGkZT0dqXHWJLu3T05ebLgC2BQ0B28vQueu7j3TRAeZJkqLZIEHk4FM0WK/C//bg5KslRa1GUU+zIGn661MPOZq6mB4LNQwB2VlENcWi4Alvm/E9Q6PYM+O4RKq8e/qROrXzQsfygciDYkB8ILficN//II4388ycTlp0o8/vStFBb+fYUx3x3n6eWnTOs3O/sUzerp39rN9LPSUs7zfZpz/J0h/Di5G8PaN6nGV2FYI+xgbVWt1xSE+kQEn4JQg06fvk3Pnl5MmhTIP/8U7Q9XnP37bxIVlUZMTDpnz8bRrVtTwDwYM7pwIZ4WLZx58cUuXL2aTGxs2WXji2NpKWfSpE0EB8ejVuvYtu0qPXt6lXqOXi+xb99NBg9uUWTf4sXHmD9/ALa2Bb9gT56Mwc/vO37/vXwpYQcO3CI6Op3Y2AxOnYqla9em9O7tzYULd7h6NQm1Wsfw4WvYs+eG6ZxGjWyIikpDo9GRnp5X5vtTkbTbiujZ04vr11NYseI8y5efIyIixfR+JifncOtWKh07Vu8XGkGozzLyA62mhYJP48yTsbqssT1FSWor+DSs+az+tNvkbEO1VC9nG3aFxtP3kwOsPR1NVv4sq6ZQMB7g6cigto15ursPmXm12/alOq06fov5f13i6PW77Lwcz1A/d7PfhSGx6ai0OlKy1SzYepnLtw2pyJdvp/PRDvNWX68/1Ird/x5odoPDqHDLk+AFI7BVWOJmr2RUoIdIjxWEaib+RQlCDXrqKX8uX07E0/MLrly5i729oswqsj17ejF+/AZ69VrB4sVD8fIqeTZz2DBDwYImTT7nzz8v4+vrYnb94goOFcfOTsHq1eN48sn1+Pp+TZ8+3owfb0gL7dHjpyLFcsBQmKhpU3uztY0Aly8ncu7cHaZPN2+4nZ2t4erVZFJT8yiPgAB3Hn10LT16/MSHHw6hWTMn3N3tWLFiDGPG/EmLFl/Rp483Y8cWzCB++ulw+vX7haZNlxISklDm+1MdabfFvT8ymYytWyeyfn0ov/xygU2bJqDIL2px5EhUmYG9IDxojLN8xvWaLw9siTw/ymicv54xLT8NVZIkNp+PLZKKa1rzWc39Pctiq7BEpdWj1em5lpDJjpA71XLdiMQsZDIYFVhQEfs/Wy6xZFc4ALGpuabtIwIMN7OaOltzN1OFSlt7rV+qQ3h8BsO/OMzCv6/w26loTt00fG4vndCJpvnrKAPzfze+u+kSj317jNUno/h6/3UiErN49NtjXMoPRP/3XDc2vdaHOSP9aOfhUOzzPdTOnf8b2oaDswdjbVW9VZIFQTAnq+mqaN27d5eCgoJq9DkE4X744IMXmTfPG4savAu6atVFDh2KZNWqcTX2HLVp/vwDDBzYnBEjWtX2UASB6Oh09u51Z9q0d2t7KA+8/WEJTFsdxNbX+9HJxxmAxTvD+N/hm3z1dGf+ve4i61/pQ2MHJVNWniEqOYfHu3ghA3xcbfn3sDa8//cVNp2L5dL7I+/r2Dedi2XWhmC2z+zPsytOk56r4fL7I7EvYc1feX3w9xXWB8VwZt5QVp2I5NNdV4s97sfJ3UwB6vqgGN7eGML2mf0J9HIq9vj6oP+SA2bBNYCnkzUn3h3Ke39dRiaD9x71x++9Xej0El7ONjRxVHI+2rwq8NcTOzO2s7jZJwj3SbkqM1btk1EQBKGcsrPV6HR602ykIAiCUVy6ISOicErkm8PaMqVvC5LzK1Sn5qhZHxRDVLKhaNiWC7dNxw5u15iUbDWu9vd31hPAL78gTWxqjmk29nZqbomzbGXJUWtZczKKXI0OpaUcW4UlMwa3Zsbg1izYepnVJ6PMjg/wLMiOMRZsevTbY0R+MrpSz18XJGcVTbEe28UQRC4aF2ja9ufLvdl68TZvDW9HtkrLgE8NyyiWPNkBdwdrBrVtfH8GLAhCuYngUxDqkClTOjNlSufaHkaNsLNTsHjxsNoehiAIdVB8ei4Wchlu9gVp/NZWKuzMjQAAIABJREFUFjR1ssHY1nHxP2EMaGMIJr6e2Jl//XnRdOzdTBUp2er7nnILBWm+cYUqXGdVYQ3oV/uus/zITayt5EVej7GCqsJSzrT+vrRtYo+Pa0F/yabOBcF74YJ19Y1aZ1jP+srAltgoLHionXuRKrUAPVq40qOFoT2Pq52C4AUjiEzKNs2eC4JQ94jgUxCEBkGr1SOXy8y+bGVnq7G7z8VHBEGouDvpeTRxUGJRTLBkLDgUmZxDZHIUHo7WPNKhqVnwma3WcjEmjYFt3YqcX9OMAeIH26+Yth27nkS35mX3Si5OQn5/zzyN3lTx18gYfNpYWTB3VNGK2YVb1Zy8mUy/1vf//agqrU6PhUzGqA4evPOwX4V6LDvZWInAUxDqOBF8CkI1iIvLZOPGK6aiMsWRJAm1WsfUqV1MRXoOHLiFp6cDfn6GLwinTsWSkpLLI4+0KfM5FYpFZGS8i7V12f+M33//EK1auTJ5csdyvqL6Z+vWcFatCubvvycBcOdOJg8//DsXL75a6nkrVpxHrdYxY0bF2sKI918Qqk98el6xVUgBlJbmn6uNHZRYWcgJ8HQkNM5QwTo5S02WSkuXYtpo1DRrKzkKS7lZK5gv913jX8PK/hy/V2xqDlsvxpkeK+8JPtvnp/j2a92o2PNtFBZM6unDH2di2HQutl4Gn4mZKtQ6PX1bN6pQ4CkIQv0ggk9BqAYKhQWeng4olRbIZDIkSWLq1K188skwPDzsAUPwqVLpsLCQoVYb/i+Xy5g37wCbNk0A4IMPDvPii13Q6yV0Oj1W+VX3XnppG337+jB1ahez57SyKr740bRpW7l+PcU0CxgTk0FOjoYVK84DoNNJuLnZsmXL05V+zb//HsK+fbdYubL0/qVLlhzjyy8LerFlZal5++1+/Pe/g0zbVq68wOHDUVUqtLR161WeeMKPd97ZZ9rm4KDk7bf3mt6H8eP96dbNE4Cvvz5FamoeW7deJTDQncTEgibu9vYKZs/ua3pc197/Tz45xuLFxwxFN94byKxZfcs858MPj6DV6lm4cHCVriMINSEhI4+2Tcq3RrJDfvrlyqk9+HLvdf44E01S/hpBW+X9r1Qqk8mwsbIo0oe0MmmvMSnmRXas7ilwN8SvCaHvjywyI1rYorGB/HEmBk9nmxKPqcuMVYsb2SnLOFIQhPpIBJ+CUA3c3Gx56il/+vf/hdxcLQ4OCgID3fntN0NPS41GT3R0OjExbwLwxhv/cPFiPHK5jGvXkgkM/B6VSkd2tprFi4+xaNERevTwZMWKMYAx0DH/UmVpKTdV3r15M5Vz5+JM7VHmzRuIra0VHh72XLuWzPTp29i79zn0egkbGytCQxOrVLV3+/ZrvP76P4wbVzTt615z5/Zn7tz+psf9+//C2LHtTI/v3s1mzpy9PPpo20qPJykphw0brvDhh0No2dIFS0s5crmMceP8kCQJSTKk5RZuW/PDD0GsWfM4EycGml1Lp9MzcuRvZsFnXXr/T56M4Y8/LnPhwivk5Wnp3XsFEyYE4ONTcmXLn346x8cfH+Xtt/tV6TqCUFPyNHpsSskcKayztyGt0t3BmoVj/PnjTDQxqYYiRHaK2vlaY6uwMBUbmt7flxXHbhGTmkPzRnblvkZ6roZJP50y23blTtHezXZlVNG1tJDT2EFJUpaq3M9dWyISs8jM03DjbjahcekseCzANO5GtVA8ShCEmieCT0GoRgqFBf7+jfH0NL+Dn5OjIT4+y/T4u+8eYcqUv3jvvYEsWnSE2bP7EhmZRlBQHNOnd+XZZzfz00+PmY4vKfUoO1vNN9+cZtmys8yc2dO0/fjxaJYuPcnmzU/z73/v4uOPh7J8+TmOHYvhww8fYsKEjcyfP8CU7ltRK1de5L33BnLpUmKFzjtw4BaNG9vRqVNB37o339zN8OFVa73yySfHUKt1KBQWpKXl8fHHx1AqLZDLZUgSaDQ6+vb14fPPR5jOkctlvPnmbizvmUGQJIoEhnXp/be1tWLt2ido2dKQXtiihTNxcZklBo3Z2Wp27bphNr7KXEcQapJapy+SYlqYrcKCHLWhd2XnZgVr+pSWFrR2tzf11ixvAFvdPhgbyEu/GtrK9fR1ZcWxW1yJy6hQ8Ln2dLTp571vDmT4l0cY3r5JpcbjZl+14PO3U1H08nWlTTlno++Vkq3GtYz19rsu3+HV386bbXvnYT9Wn4gEwNet/O+dIAj1R7mCT5lM5gp0Ay5IkpRUs0MShPpLLpdx7twdrl1LNtuu0egxxi86nR5Jguef78T+/beKXGP9+lDmzOmLTicBkik4+r//28ncufvIylLz3XcPA9Cx449MmhRISMhruLoWpFg991wn2rZtxNGjUcTFZTJr1h4aN7Zl3bqnCA9PYvnyR+nXr1mlX+fGjeNZvTq4wud99dUpZs3qY3q8d+8NYmMzWLBgUKWuB3D5ciJ//RVOr16GMvyPPtqW0aPbmgWVxjTmwuRyGaNHt8HGxspsu14v8c03p4s8T115/wsH7nFxmcTEZBAY6F7i8XZ2CjZtmsDChYeqdB1BqAl5Gh0hsenczVShKCUb4KF27uy4ZAgwWzW2N9vn7WJDRKLh5l5Ve2tW1nD/JvRs4cqZyBRToaGbSdllnFXgt1NRLNkVDsCoAA983ey48N7wSqcRu9kruFtMu5LySMpSMf+vyzRzteXI2w9V+PwTN5J45qfTrJzag4faFf1M0er06CWYszGkyL7eH+8nM09LM1dbs8rHgiA0HGV+SstkMhdgO7AD+EImkw0BPgH8gR2SJH1Ys0MUhDoqJQVOnoSQEFCrQaFAm6DgybGBtAw0b2qdmani44+PAYaU1SVLjpsVJ3rjjX+KXP7TT48zdWpn0zrDb7552KxgzcyZOwkJebXYaq6ZmSrWrQtlwoQA/v3v3pw8GcOCBYN56KHVfPnlSN55Zz/ff/8IHToU3FX/4YezqNU6/vWv3mW+9MoUgYiNzeDmzVQGDWoBQG6uhrfe2sPmzRO4fTuzwtcz0mh0vP/+YH76yXAH/e+/r7FgwSEsLeXIZIaZTL1e4qGHWvDFFwXN53U6if79m+HgYP4FR6fTm61RNapL77/RvHkHeOWVblWu6Ftd1xGEipr00ykuRKcBRdc3FrZ0Qicy8jT4eTgUqYhrUyglvrK9NavDiinduXw7HVc7BTKZIbAur/l/XQZgSt8WLBxjSN93qcK/x8b2Sk7eSC77wGKcvZUCQHRKTpF9kiQx+ptjXLmTwbJnujK6Y9Mix4TeNqQKT115lluLHzH7faHXS0z++TQhsenkqHXMGt6W89GpNHZQ0trdnm/3R+Bip+DLpxtmyzFBEMo389kReEuSpFP5gegQwEKSpD4ymewXmUzWRpKk6zU7TEGoY65fh/XrQa8H44yaSs38bhrW7jzNjp2NmDmnoKCOg4OSr74yBD5jx/oxdqwff/99tcSgy93djieeaF/mMIoLFnQ6PQMGrGTGjB5cv57M0qUnsbW1YsqUv/D1dWHLlnA++2w4K1ac5+uvHzadt25dKFlZ6goFPxWxdu0lJkwIMD1+//3DPPdcR9q0aVSl4LNLl6Z06dLUFHyOG+dXrrWoXbp48N57B4vd16OHZ7meuzbf/507r3PsWDQXL75SruNr+jqCUBHno1NxtLYyBZ5AqUV0rK0sWDOtV7H7MvIMay3/b0jrWp0tc7S2om8rQyq9taVFuYNPSZJMP5f2HlTExdg0tHqJ9UExTOjuU+7z1Fo9r/1ekAq789IdbBQWuDtYYyGXseLoTdM61NkbgmnmaotfUwezGweFU587LNzD+2MC2BeWQFqOhpM3zQNiLxcbZg4tqAo8uXdzLOSyIhWOBUFoOMoMPiVJOgwgk8kGAj0BV2B9/u49QH/ALPiUyWQvAy8DNGtW+dQ+QaiTUlIMgaemaBPxpCyJP0OgpWsSP353Ciwtyc7WEBmZxp49k82O/eabM4wZ0xZfX/PWAHfuZPLFFydLDD51Oj1phZqZ30uS4ODBF3BxMaSBPvdcJ+bPP4CHhz2vvNINuVyGhYWcbt2aotXqTemphw5Nqci7UGGbNoWZrWP9++9rJCXl8MUXJ1GrdeTmasnIULF5c+Ur8ALs33+TSZM24e/f2LQtKSmHESNamWY+1Woda9c+yZEjUXh5OZCZqSYuLtPU4mbv3huoVFqUxaTw1YX3PyYmnenT/2bLlqerNFtZXdcRhIp64vsTADSyU5CcX920uB6f5fH+mAC+P3SD1wa3rrbxVZW1lZw8jb7E/TtC7tCnVSNc7RTEZxR8nmSriv5eqYxXB7bi7U0h/HXhdoWCz/h08882YyDa2EGJo7UlN+4aUolXTe3BS78G8dh3x5g7yo9O3k78HRLHnfQ8U9A9ppMn24LjmLWh6JKKpeM7ceVORpG0XNtaKhglCML9U941nzLgaSAVkIDb+btSgK73Hi9J0nJgOUD37t2le/cLQr128qRhxvMeb+6CK0nwy1j4/CR8PdEZ9ydHMnHiJn7+eQxdupinJ1lZyfnuu7PY2Jj/M1Srdbi7F19oYdu2q7z77n7mzCnaEmP9+lAefbQte/fe4JNPjqMstFbo1q00FAoLNm4saIKu00m8/noPU7XXyqR9lldycg63bqXSsWNBmmlo6AzTz4cORbJq1UVTq5WNG68wf/4BfvzxUQYPblGh57KysmDIEF/+/PMp07a//grn1KlY0+MxY/7gww+HsGZNMCNHtsbfvzFvvbWbUaNaI5fL2LQpjN9/v1Sk9UtdeP9VKi1jxvzJnDl96dnTq9Rj78d1BKEqvFxsTMFnZbV2d+CLCXUrTdPaquSZz8TMPF5fe57eLV358+U+XE8oKEbX8p71rJU1oYcPv5+J5mJMGuejU+narPT+p3uvJKDW6vHOv2k275H2fPRPmGn/3UwVdzMNBYxmDG7F4Hbu7H1zEIM/P2Raq1rYUD93vpnUhSe6evHtgQgWjQ3kkW+OArDi+e4M82/Ck9XySgVBqG/KFXxKhpyQ12Uy2SLgKeCn/F32QPXkiAhCfRESUpBqW8iiIWCvMOyylEO/WaFYzIvgnXf6MXJk0Wquer3EunVP0bmzh9n2iIgUpk3bZrbt2rVk1q69RPfunqxY8Rh9+vgwa9Ye4uOz8PCw58aNFCZP3kxc3CxTWm9hxpm3N94wr3haWHWk3Xp4fE5U1L+LzBgeORJVoQAnLS2Pq1eTyapAwQy1WockSchksGfPDbp3X252vSefNMwkx8SkExGRQrduhpsBMhn4+zcmKOhl5HIZ48dv4JdfxjBkyK+cPBlDnz4+der937UrgosX47lzJ5NPPjGsI1627BF69vRi9Oi1hIS8Vq73q6TrPPmkf7nOF4TKKpxmmpRZ99uBVEaWSsu56NRi92XmGWY3T91MQZIkUnMMn3OfPtWRp7p6V9sYvF1sCI5J44nvTxD5yehSjzVW6jXq2tyZZ3o1Y+3paIb4uXMg3FDZfMuMvnTJD2RbuNkR6OXI5fw1no0dlMx7pD3HI5L4v/xU2sHt3BmcP7s5uXczGtkpGdpeFDYThAdZeQoOzQXuSJL0K+CModhQf+AU0Am4WqMjFIS6Rl00IIrNgFl74E4mRKdDJw9Y/ii0nvscW7aE0afPz2RmqnF2tubHH0fTrZsnGo2eZ5/dXGTmU6XSYX9Pf7OJEwN5660+jBpVkFb2yivdGDJktamR+aJFD+HmZlvskDUaHZoy1h9VNO12ypTOTJliPtsQHz+72GMff7w9jz9e8hrWwYNbmM1wTp/elUOHImnbtlG5x5OamodarUOj0TNiRKsiM59HjkQBhiB16dIRyGQy2rdvzJw5e00FhnJztbi62uDgoOTo0alYWxv+bOrS+z92rB+StKDYfaUFngsXDi73dQShJqm0BTfv4tLzsJTL0OqlShUyq6sy87SmIPNexn6gAIeu3jUdN6htY+SVTD0ujo9L8Z9HhR25dpc+rYp+zrZ0s2dq3xasPR3NjMGtOBCeSEs3O1PgaTSlry+zNwQzoI2baU3uuC7F32j8cFyHSrwKQRAaGlnhO5DFHmAoMrQeUAKXgXeBI8B+4GGgtyRJ6SWd3717dykoKKik3YJQbyxaNJ133/XE8rMloCoagB6NghbOYGqTqFTAu++a9qtUWiIj02jXrnK9NR8kt29n8Ouvwbz77oDaHorQgEVFpbF/f1NefHFubQ/lgZKYmUfPj/abHjsoLclUaZk1vK1Z8Zn6bNRXRwiPzyxS7RUMbVWM1W0HtHGjbys3luwK58oHI6t1zWOWSkvggt0Axc58Hr1+l+d+PsOs4W3582wMt9NyAfOKu0bBMWn4NrbD0dq8NZUkSZy5lUKglxN2tdTmRhCEOqNcd8/KTJmVJClVkqThkiQNlCRpRn6gORjDzOdDpQWegtCQKBTWqFRa6NgRimkJMKB5ocDTQg6dOpntVyotReBZTl5ejiLwFGqcSqVDqSx7dkioXhm55jOCxtjMspRWK/XN2M6G2b97iw7dvJtlCjwBEjLyuBCdioPS0qxlTHWwV1ryxkOtkcvMU52NIvP7kN5Kzkal1dPEUYmVhYw3h7ctcmwnH+cigScY2m71atlIBJ6CIJRbpT7p8wPS9ZIkxVf3gAShrmrSpCWxsRnQpw/Iy/inI5dD75ppWSIIQvWIicnG3b3oemyhZmXmacweG1NNLasx5bS22een7GeqNEiShCRJbDoXy5ClhwHo1tyFp7p5cy0hiz1XEpg+oGWNpB272SvQS/Dab+cJjSuYK5AkiZv5wWd0cg4ZeRrGdvbi+keP4GRTNMgUBEGoLg3nNqMg1DB//36EhmaDqytMmABWlkj3flmykIOVpWG/q2vtDFQQhDJJkkRoqERAQN2qkvogyLhnLaTxU9TSouEEn475wWdGrpbei/fz0Y4ws5Yj748JwCH/mMYOSqYP8K2RcbTzcARgV2g8o785xpYLhqrfv52KYuXxSMDQc1Wt1RPg6VgjYxAEQShMBJ/1kEqrQ6cXHWzut4CAQG7edOHy5URo0wZee41kvw6oLCyRAI2VFXTrBq+9ZtgvCEKdJEkS+/bFYGPTnqZNm5Z9glCtEu7pJTm1ny/OtlY8HNhw/izs89NQz0elkpChYsWxW2b7AzwdcbNXAvDvYW1qLG21d0tX5oxsZ3r85rpgopKzOXT1rmmb8etEYwdljYxBEAShMJGkXw+1m7+LRzp48P2z3Wp7KA8UOzs7nntuLmvWLCY6OhJ/f2cutevJDdcAbBUWeDnbMrpjw/nyJAgNjVar58aNFC5ezCA11Y/nn3+jQVVYrS/e3hRi9ti/qSMX/zuilkZTMxzy10f+c/lOsftlMhnTB/jS0duJfq1qrhaATCaje3PzCrWDPjuEg7Ul1lZyRgZ4sPViHECxazoFQRCqmwg+65nU/Gbc/1wSy21rQ5MmTZg+fSHBwed5//u/OHf1FgqlDCcbK+yUaayzvUvYnUwAxnb2xLqaC0gIglA5Op2EWi3DxycQf/9+jB3bCWtr69oelgBYWTa8JCzjzOfZWymmVjIAfh4O2CgMvxeUlhYMaNO45sdiXfBV76UBvthYWbAuKIaevu44F1rfKdZ6CoJwP4jgs54Ju5Nh+rnFOzs4/Z+hNHEUX6DuJ2dnZwYNGsLe1MYc4BaSVkOz5s4AHIpKhfwWZ91HdaN/MV8s0nM0ONmKX/KCcD/J5XKsra2Rl1UsTLjvrBpQoSEj43rObLWOjt5OhMQaiv0sHBNA75bl719cHZo3sqOzjzNPdPXi+T4tAHhzeFtkMhlP/XDCdJxIuxUE4X4QwWc9otHpee6XM2bbIpOyqz34TM/VMHTpYV7s34IZg1tX67UbEmcbBTK5BTKFBc5OjiRm5mFrZ2cqrW9rZ4+9vb3ZOX+ciebdzZfYPrM/gV5OxV1WEAShQevk7URwbEHl1YY88wnQyE6Bu4OSxEyV2fb7OZa/Xu9nts2Ybv7a4FZMWx3EvEfai0wdQRDuCxF81iPno1KLFBpSafUlHF05G8/FMju/It+nu66K4LMUWaqCio3NXG05EJ5otj8917ydgEan593NlwA4dTNZBJ+CUIO+WLyYkHPn8OvWDb/27fH396dt26L9C4X7T62TsFdamj5DG2K6Z+ECQjYKC5Y/350lO8Np7W5fyln339D2TYj8ZHRtD0MQhAdIw7vd2IDFpecC0KdQyk7mPSXrq+KjHVdMgSeAjZUFKdlq9KKybrGMwaXCUo5/MSXqQ2LTzB5PWVkwa52ao67ZwQnCA27ljz/SctMmkv/7X35+4QU6BgRw8eLF2h6WgOFGnGOhdYht6lhAVh0UlnKU+TO6lnI5nX2c+ePl3mJ2URCEB54IPuuJkNg03lwXjNJSjluhdRkZ9zTrriyVVsdPR81LwedqdHRdtJfvD0VwKymbXLWuWp6roUjNUePn4cDlhSNp7moLwAdjA/hgbAAAR64lmR1/PCLZ9HNKdvX8uQmCUJRWqyUiLo7ZwGdaLdsyMrCWy/H29q7toQkYgk9XewUAT3b1brAVh43rPq0sxFctQRAEI5F2W08Y0zX7tXZDpy9Itc3IrXoQk5KtJjolx/R4z5sDiU7OYfqvQYAhFffzPdeQyeDqoodRNMD1OZWRkq3G3dEahaWcDt5ObJ/Zn9bu9lhbWZCareHLfdfI0+iwtrIgNjXH7Nw0MfMpCDUmMjISD6USW60hMyQBsLSyws2t5lpaCOWn0epp7+HI/NH+RdqANCR2SkuSstQoLBtmcC0IglAZIoqoJ4wB3/tjAribqTJtr2ra7ambyXRdtJdxy44DsOyZrrRt4kC3Ql8IslSGGU9JgoSMvGKv86DR6yVuJWWbZjxtFZYEejmZUqqcbAz3dVYcvcnT/ztp6qM2qacP/k0d2Xk5ngn/O4kkiZRmQahu4eHhtLcoSG8MB9q3bFl7AxLMqHUSVpZyerdshGUDnhU0FheyFBWWBUEQTMQnYj2h00s81K4xPq62TO7dHAArC1mV0m7vZqqYuPyU2baWje0AcLFT8NHjgQDYKwu+xN3NUiHApdvpZOZp6ZrfYuVetgrDl47P91zj9K0UPtt9FWsrOYuf6Eiz/ID1zK0UMlXVt2ZXEASDsCtX8MvNNT0OB/w6dKi9AQlmNDo9igYcdBoZg0+RdisIglBAfCLWE2qt3jT7ObazF5GfjKapk02V0m7j0nKLbCvctuXZXs1xtLZEoyuYnUvKFMEnQGRyNgABnsVXrDU2ES/M2ILFy8XGtO2ueD8FodqFnz+Pn6bgszFMocCvS5daHJFglKfRkZGnaZAVbu9VsOZTpN0KgiAYieCznlDr9EXunjraWFYp7fZmUlaRbS625l8IXO0U3C4UpH6x9xphdzIq/ZwNRVyaIf3Yy9mm2P2WpTRNf6RDU9PPn+++yomIJF745Qzqam6bIwgPqvBLl2hf+LGNDX7t25d4vHD/xKbmIEng62ZX20OpcXZi5lMQBKEI8YlYTxSe+TRyUFpVKe02JL/Jd+Hr3lt10O6ehtjh8Zks3hle6edsKG6n5eBsa1Xk/TFq3qjkL1advAtmS3eHxvPMitMcvnaX+HSxnlYQqkqSJMIiI/ErtC1cq6W9CD7rhFy14SZbSZ+dDYltfgaMCD4FQRAKiE/EeuB2Wi7JWeoia2QcbSzJyK3czKdWp2fl8UhaNLLlrxn9SjwuvVBa7zsPG77OpWaLSq23U3NLnPUE8Pd0JHzRKN571J+ZQ1oD0DE/6LS0kPNsr2a42Ssp3EI1UyXarwhCVd29exeZToexrm0WkKhS0bx589oclpAvT2soYGdt1fC/figtDcGnpUi7FQRBMGn4tx7ruXVno5m7ydBm5d67p68OasWtpGxiUnLwyS9iU14htw2znk0crU3rUooTm2pIud35rwG0b+pISraa5Udukp77YKzZKcnttNxSZzcBrK0smNbfF4Cnunnjaqcw7fvo8Q78a1gben6037StqpWLS5KWo8bZVlH2gYLQAISHh9Pe2hqZyrCe+hrQxssLC4ui67CF+0+Vv/bdGJg1ZMblF6UtwxAEQXjQNPxbj/VYdHKOKfAE0N/TlqOjtzPLDkYw848LFb62Mah871F/3OyVAPznEb8ixxkDzHZNHADwb+oIQFKWCr1e4qcjNx+4ojm3krK5lpBFB6/iiw0Vp3kjOxyszYN1dwdrUzVEgKwaCD6X7Aqn8wd7SRJVioUHRFhYGH7qguyMcKC9v3/tDUgwo8qf+VQ+AP2iLfKDTtFQSxAEoUDD//Svx07dTDZ7fPpWitljC7mMQW3duRJX8QJAt/ODT183O2wUFtz8+BFeHtiqyHHbZ/Zn+8z+yPN/ibrkz96lZqu5EJPGR/+E0eOjfUQkFi1e1FD9ejISKwsZE3v4VPlal98fyYFZgwDIqua2Kzq9xA+HbgCQmCGCT6HyJElid2g8Gl3dL4oVHhxs1mYlTCbDr2vXWhyRUJgqv7CasSdyg5Y/4XnvjWNBEIQHmQg+67CUHPO1lS8N8C1yjKudFWqd3nQ3ubxiU3NwKVQwR15CWpCPqy2BhWb43OwVuDsoUWn1RCZlm7ZPXnG6Qs9fX2WptGwIimV0h6a4F2pLUxXGGdHMChaP2h+WwIQfTxZbJTc9V8PR63dNjyt6bUEoLCgqlVfWnOOjHWG1PZQyhV+8aF7p1t4ev4CAWhuPYC5P8+DMfMrzC/iJ2FMQBKFAw//0r8dyCs2EDfdvwtM9mhU5RptfseZgeGKx15AkqUgV1fQcDb+fjqapU8kFc0oS4OnEmXnD6NfazWymrri+lg3RpnOxZKm0TOlX9EZAZRnX3L63NZR3N4eg05fvm8q01UGciUxhf1iC2faMPA3dFu1lysqzpm2/nY6utvEKD57s/H/ru0Pja3kkZQu7ds280q1MJird1iGRSdnIZQVZNA2Zb35QH0rEAAAgAElEQVRdAE/n6rlRKQiC0BCI4LMOy1HrsFVYsOAxfz5+vEOxxxgDy2/2RxTZl5Slwvfdf+i9eD9RyQWzlB/uuAJAa3f7Ko3PGHx28nFGrdWz7mzDD3CORyTh62ZHZx/nartm4RmAP87EEFnoz8pIrdWz6/IdpPxb6CmFKg7n3TPrffjqXdNNCaO/g+M4eDWR4V8c5tj1pGobu/BgmLrKcCPjTnqeWd/fuiYnJ4fE9HRa5D/WAhE5ObRt27YWRyUUtudKAt2buz4QBevGd/dmzbSejOvsVdtDEQRBqDNE8FmHZat12CosmdrPl8YOymKPMbY/6enrWmTfh9uvmH6OSzMEqSnZarYGx9HZx5kFj1WuCMe+Kwm0eGcHn+2+CkArNztup+Uyd9OlakvvlCSJp344wU9HbpoCrrogLVdT4p9FZclkMl4Z2NL02FgMqrDvD0Xw6m/n2XslAa1Oz9nIgvW/6Tnm7/m+e2ZCe7Yw/N2YuvIs1xOzOH3LfC2xIJQmKjnbLG3wuwNFb3TVFdeuXaO1rS3GPIxIoImzM7a2FasGLtSM1Gw14fGZDPZrXNtDuS9kMhkD2jQu0j9bEAThQSaCzzosV601NakuibOtAv+mjpyPTiU83rzwUOEZiu0hceSotaw7G4Naq+fTpzrSyL5yQZRFofWh3Zu70K2Fi+lxjrpia0/vpdbq0eklrtzJICgqlY/+CcP33X+IScmp0nWrw+7QeM7cSiG3iq+xOO887Mfbo9oBcPNu0eJNxoD05TXnmLUhmISMglTq5EKzoBqdnoPhiTzVzZup/Vrw2VMd+emF7rgXCphrqqWL0DCFxKabfh7fzZsNQTF14t9jccLCwvArFCmHA+3btKm9AQlmovP/3rRuXLWsG0EQBKH+EsFnHZadn3ZblgBPR0Ji0xn11VGmry5Y53e70Aza76ej8f/vbn47FUWflo1om986pTIKr9VZ+1JvJvVoxiuDDDN3N6pY9XbqqjOM+uoIQZGpZtt/PnarStetKEmSeO7n02w8FwsY2gO8suYcAE2dqn/9jkwm47VBrXCxteLTXVdJzTYvNnXyRsFs5e7QeJKy1Mhk4O1iw638wk/ZKi0hselk5Gnp26oRCx4LYHx3H5xsrPh7Zn82vdYXH1cb0u4pZCUIpclRG25WnHhnCLNGtEMul9XZ2c/w0FD8sgo+g8IAvy5dam9Aghlj8NmskZiJFgRBeFCJ4LMOyy1n8Fm4Gm1QlCFoOxCeQNw9hYbAMBv6Qt8WVRqXm70h+Ozo7YTCUo5cLiPQ0zCGZ1acrvSsyMGriRyPSOZ6YhYLtoWa7dtx6U65C/FUh8RMFUevJzF7QzDrzkbz05GbAMwc0prPxneqkeeUyWToJcjV6Ji/9TKZeRqikrPZEBRjmsUe1r4JzVxt+Wb/dSQJxnX2QqeX+PNMNAELdvPkDycAisxqN3G0pltzF5q72vHXxTge/vooG4Ji2BYcVyOvRWg4slWGmX47hSUeTtY82dWbLRdv39d/j+UVfu6c+cynrS1+HTvW4oiEwowZHN4uIvgUBEF4UFmWfYhQW7LVWuwUZf8RBXo5mn42Fq85mz9zuPiJDqTlaFiyK9x0zLD27lUal7eLLd8908Ws6E7hPmYDPj3I1Q9HobCQo9NLfHcwAisLOTMGtyp17cvCewLOwu5mqohNzaF5fvXAmnYtIdP089xNlwDo5evKrBHtavR5e/m6sudKAjtC7rAj5I7Zvm7NXXCyseJagmFmx9vFhtkj29HinR3svGxehdTRuvi/N+O6eHEsIomwOxnM2RgCQEs3O7MbGIJQmHHm01jRuqO3E3+ciWbvlQRGBXrU5tCKCAsL451Cj8OtrHhBVLqtM9Jy1Cgt5dgrxVcPQRCEB5WY+azDyjvz2b5pQfCZkKFCr5fYH5ZA12bOTOrZjKd7+Jgdb2lR9T/2Rzt6mt29Ht2hKR89Hmh6/PzPZ/jPlku0nreTr/Zd57PdV5nx+3lTy4bieOa3funSrPhKsmtPR5OZpyEtR12kfUx1MwZ4hY3p7Fmjzwnw32KKQH3yRAc+GBvA79N7Ya80/H1wsLZky4x+RYox9W/tBoBbCet5n+zqZVbcCCCoUPGi4sSk5NDjo31cvp1e6nFCw5Sl0mFlIUORf2PL+HesrlW91el0XL99G2NdWwkIy8vDz8+vtNOE+ygjT2tqLSUIgiA8mETwWYdlqcouOARge8/s6Pytl7mWkMUTXb0BcLVTsHJKD6Dqs54lsbSQ82yv5qbHZyNT+ONMjOlx80a27A6NZ8L/TqLR6YucL0mGIkOTejbjm4ldeG1wK/a+ORAoSPP935GbTFx+ikGfHaL34v018jqMQosJtEb41/wsz73paGEfjGJiz2Y836cF1lYW9PRtBMC/hrYxVd3t3txQ8GnG4FasmdaTM/8Zio9r8WltMpmMdx724/+GtuGFPs1RWsoJiU3nrfUX+Ty/evG9Zm8I5m6mike/PVanKg8L1U+j0xf5M45JycHTuaAnsHHNc3VVtq4uUVFRuCuVGHMj7gJYWNC48YNRWbU+uJupwsG64bdYEQRBEEombkHWUZIkkZylrlRF2j/OGPptFp6pe8jPnfPvDcdOWXYwWxUv9GnO6pNR3LscbPETHQi9ncFH/4RxJy3PVHBCp5d4c91F5DJIz9UQ4OmIj6stc0cZZit+nNyNDt5O9PvkAAChcQUVffV6Cbm8+kvYa3R6zkWn0sHLiVtJ2fz0fHeyVdpqb7FSkj9e6s2kn04xuF1jU6qj0eiOTWnZeICpYJRMJmP58905F5XKcP8mALg7ll4QSSaT8dZww/zQmchUNl+4bdrnZq/gmV7NTbNckUnZnL5VMDO67GAE0/q3LDIuof7beyWBl34N4vk+zbGxsmBSz2a0cLPjemKmWXVSSws5tgoLrsRlMH11EF9P7IxdHUijDAsLo71Fwd/LcKC9r69oc1FHSJLEvrAEOnqLFH9BEIQHWe1/YxCKlaXSkqvRmbXIKM2m1/qSnqvmxVVBSBLYKy1xvOcOs2uhKrU15f2xgYwM9OCZn06bbW/bxIGkLEOVVbWuoFXJP5fumBW9+f/27js8imp94Pj3pPeQQBIILRBK6FJUOtKkWLGgXEXFXrj+7ILda0evvYDXgnr1KopdFJDeIfQWSiB0QhJIIT2b8/tjZje7KaRs+r6f5/ExOzu7nLyZ3Zl3zjnv6dLCsQqvdU7Z/43syC9bjpGQUlTMKOlsLhHlJFpV4enuxoIHh5KdZ6GJX83HrLgB0U3Z9PRompSxCLv9MGsw/q7WxLOybh7Qlmk/brc9fu63XSyKO8VXt13IV2sSePoXYx7ujKt78s6ifbyxYC8fLo1n5eMjauV4ErXnv2sPAfDlGuP/s5YfoFWIL0fPZJfo9Q/29WTBLmM92YW7Ermyd8vabWwp4nbvJia7aCjwbiCme/eyXyAcnDWnRNTUfMwT5lSJizpJT7QQQrgyGXZbT1mXGokplmiUpW/bEEbERNiG6ZZVcKY2tC42dPSlCd1pFuCNlznXNLfAGHa78dBp9tkV9gFoE1p6QaEHR3fiwdGdHLYdPVN2Vd3DKVkMf2Mpaw+klLnPuXh7uNdJ4mkV6u9VI726xV1/QRvm3jOA+0d0sG1bsS+Z6z9e49DL3C8qxDbHLyvPQp8XFsoQ3HPQWrPzeBrJZ3MByMm3sDgukV1mTFftT2brkdS6bKKDvIJC1h8sOffXWp30Hxe2cdhuP6zb2bV9q8vuTZuIyS8aChzn6UlMnz512KKGIy07n+7PzmfIa4ur/b1zCyy8tXAvy/cmATCssySfQgjhysrNUJRSwcC3gDuQCVwHfAR0Bf7QWr9Yoy10QTn5FqbMNtbrvLBdaKVeG+jjQVaehaAyes1qQ3O7dTCfuqSLbS6ot6eRfK7an0xOvoWrP1pj2699mD8HkjJpeo7etOJ35GctO0ChPsDLV3UnPLDo38wrKGTo60sAmPL5BnY+P6ZWErmGqm/bUHq3DuGmgVH8uf0ET/+yk7UHTjsM+Q4L9Lb9jayW7klieEzNzCFu6L5ae4hnzF7j+Q8MZew7y7Hm6l/cegE3f7YegIOvjAeo86GhW46kkp1vwcNNUVDKEir2cz4Bbh4QZUtWz+bWj7mfcdu2Mdnu8W5fX0Z2LVnAS5Q06s1lAJzJyqfAUliiKN3JtBzOZOWVGHVREb9tPcE7i/bZHnduXvn3EEII0XhUpOfzBuBNrfXFwEngesBdaz0AaK+U6liTDXQluQUW4pPOMsxMnAK9PfDxrNzcOmuCVnzIbW3ytLtwuW1wO9vP3ub2l+fFOSSeAHPvHkjcC2PPmSQWL6y0YFcif+9O5Kmfdjhs33+qqFJtu2b+JGfmVv6XcDFubopmAd5MHhDFv67oxoXtQknOyOW81k3Y+uzFBPp48u0d/Zlz1wDem9QbgCmzN5CTXz96veoba+IJMGt5PPadxNbEE+DzVQm0mz6PL1YnsCHhtG1Zk9q29kAKSlFiDeC59wxgxWPDS+x/Sc8Wtp8T0+vH5ysuIQH7urZxFkuNVLrdcSyNT1cerPb3rStHz2SRlFH0N7zps/VETfuD37cVTYe4dtZqxr2zokojSXbZjaBo2cRXllkRQggXV27yqbX+UGu90HwYBtwIzDEfLwAG11DbXM6+xLOM/Pcy28Xc9PGVX58uxBwqWpc9nwALHhzKr1MHOfToWIvYlMa/Aol2lxaBDOnYjB/uHuD4b+1KJGraH8xcFs9fO06yJ9G42PnrgSH8/s/BDr2ionwT+7Xm0l6R7DyeTligN8HmsRQe5MMF7UK5rFdRIatrZ67hyOmyhz8Lo1cRwN/LHf9ihZr+9fsuAJ79dSfXzlzDJyvqJqmJPXSGTuGB3Gkuw6OU8Rnu2za0zMrJ1gran648yIdL99daW0uTlJSEpaAAaz98FpCYm0u7du3O9bIqeXzuNl74fRcHkkoux9QQ/bndcY3g1fFGgjn1m83kFlhIy8rnyGlj+PX1H6+tUJXjjJx8nvhpO4vjEll3sChhlWVWhBBCVHjOp1JqABACHAGs5TFPAyUqnSil7lRKxSqlYpOSkqqloY3ZjmNp/L0r0aHHEIx5nJVlHR4X5Fu3J/lOEYH0bOW4Xmfx5DPU34vr+rWmd5sm50xMrZr4efHVbRfSL6r0ociv/hnH3f/dyHuL9uPprogOC5DhtlWQkpnH0z/v4GxuQYn5u1Y/3TsQgO3H0vhoWXxtNq/e01rjpuCWgVH4e7lzICkTH083djw/hqWPFvUi3jGkZGJ0vA7WzrQUatYeSKFvVAgRQT7MuKYnCx8cZquoXJbhMeG2GxMz/tpT6hJKtSUuLo4uPj5YP+17gA6Rkbi7V39VZuvc53u/3mQr0tOQrT2QQrtm/hx4eXyJ50a8sYxPVx4AYJxZ/O3mz9YzJ/YIy/aWfW5fE5/CN+sOc+vsWHYeT2dQB2OJqNqqGC6EEKL+qlDyqZQKBd4DbgXOAtYJQAGlvYfW+mOtdT+tdT9ZY618n69K4PYvY7HYzbX65b5BdG5+7ou/0rQMMf40gfVwaJO3R9GFoKe74t3re/PaNT356d5BlX6vlY8XXcS/dV0vh2qvB5Iz6dEyuEQyLyqmZRNfhnRsBsCorqXP6ewaWTRv65t1h2X4rZ08SyGF2rjQHhBtXHRPGWQs+WF/8f3E+C5EmUsOtTF7F60VoWvTUz9vJ6+gkPNaGzeLJvZrTYfwgHJeZSi0G088be52Vu5LZs6GIw7fZbZ9S9lWXeLi4hyLDUGNDLnNKygkNcv4d+JOZvDXjpPlvKJ+01qzIeE0F7YLxc1N8fo1PfnXFd2IfWoUYCTa7y7eT7tm/rw3qTejuoSz6XAqj/2wjZs/W8+2o6mcSMvmgyX7OZ1ZdOx+v/Go7edr+7bioxv7csvAKJ65VObgCiGEq6tIwSEv4Htgutb6kFJqI8ZQ27VAL4ybzMIJD4zqyC0Do2gdWlTUw/7ivjKam0uP5OTXXS9EWTqEBzCxXyvG9WjB8M7OFappFeLHqmkjiAz2QSnFyC4R9HxuAQBbnhmNQno8nfHu9b1Zvi+JAe2blvq8t4c7Cx4cytyNR5m1/ABnsvJoEexb6r6NzZsL99IhPIDL7YYf28s2q7/6errzwKhObDuaxjV9W9meX/LIRRxPzUYpxU/3DmJPYgb92zflttkbzlnBuTTWisNVKViUkZNPfFIma8xhlqO6VH65Hg+7kQVzNx1l7iYj6dibmMFTdonG9qNpXPb+SubeM7BKIzrKs3vrVmKyimIXpxRd+vWr9n9n82GjCnn/9qGsPXCaR77fSu82TYgOq1iyXhVL9pziiR+3s/jhi6p9fd1TGbmk5xTYzjfX9mtte27t9JFM+HAVyWdzmXvPQDzc3XhifBf+3n3Kts/l76+y/bwmPoW+bUPYejSVk+ayKs9c2pWukUEE+Xjy3OXdqrXtQgghGqaKdA3dBvQBnlRKLQUUMFkp9SYwEfij5prX+GXk5PP1usNk5hU4FGKoaq+ddRhcRj2pQGnP3U0x45peTieeVi2b+NouuoN8PPn9n4NZ/8RImvh5EexXt3NeG7oQfy+uOK/lOZOaThGBtt6y1Kx85u88yamMHFKz8io0L6whSsvO591F+7j/f5vJtxSy41gab/+9l7kbj5Kek09hoSYjxxiK6eflTveWwax/cpRDctKumT+DOhg9yyH+XvQ3E/xWIb4cO1Ny2G1aVj4pZx2L+uw4lkZOvoX7vtnEtTPXcCw1m/v/t5k/t5+o0O+hteaKD1Zx5QerSEjJYnjnsCqt2/qfm/oxrntzpo1z7GX8ZOVBCuyG4c7fafQQWodwVre4zZuxnyG/29+fmG7Vn+z8vOUYbsq4OWM1ceYacvIt/Lz5GHcUG8Fy11exTPhwVWlvVWGv/RnHibQch0Jq1cX6nqUlz82DfVgzfST7XhpvOzbahwUQ98JY2z6tQny5qndLwgO9Wbk/mXcW7WPpniTiTmYwvkdzbh3cznZ8CyGEEFCBnk+t9UcYS6vYKKV+BUYDM7TWaTXUtgYrr6CQ/6w4wMR+rcud47I47hQzl8Xj5+VO//ZN+fLWC8qda3Uu1mG3zYNcoxfKXveWwXXdBJdjXQt129FUHp+7nYHRTVl7IAVvD3d2212k1jeFhZrsfAv+lRyeHm9XZOblebv5fFVC0ZPfm9sn9ACo8NBVq1YhfmTkFvDb1uMORZ0mzlrDnsQMfr5vEOe1bsKyvUnc/Nl6/LzcbWtsDnrVWJ8xNuE0Y7o1L3eu84HkTIdlc647v/U59i5bv6hQ+kWFkpNv4dU/4xyem/rNZmZO7gvAjuPGaWLTIaP4UnySUVztp3sH0ruN8z2hcfv2OVa6dXOrtmG3+ZZCLnl3BUM6hvHthiMMjG5KeJAPA6ObsvN4OimZeRxKyeKB77YA8PfuREZ1ieDamavZdNj4fQsLdZXnn1tvKO5PyqBHq8p9x+04loa3hxsdyzinWI/nyhyrPp7uvHVdL9qE+tt6sa1/z2BfT9Ky8237CSGEEMVVqXtNa31Gaz1Ha92wJ7zUkNmrD/L6/D28+MeucveNT8rETWGrMjm0U5jDOpmVdX5UKB9P7stjYztX+T2EqKiukUG4uyken7sdgL2JZynUkJ1vcZgDVp/sOJZG+yfm0e3Z+ew5mVGh1yyJO8X2o2l8vioBN2VUg3VIPO18svIArUN9Kz28dEgnozf0n//bzGt/xdl60PYkGm28/3+bAdhiJjTFe5TaN/PneFoOiRk55f5b1t7Z8T2as/7JkYzt3qKcV5ybj6c7fuaQ0BsubAPAXztPsmDnSYbMWMzSPUZxmjNZeWTnWRj5b2NdyQkfriY24TQj3ljKgp0nHZb3qKjs7GxOnDmDtXyTBdiXlUXnztXzHXggKZO9iWf5dOVBtIZ7hnUA4Js7+vOfm4yhvW8sKJp9ctdXG3l30T5b4glw2ImK0DHm3P8Xf99tG2ZdEW//vZdL31vJJe+utB1LGTn5fLBkP9+sO8wnKw7w46ZjBHh7EF7JQkATerdyOL6jwwLY/a+xbHlmNP+7o79tmxBCCFFc/atK0wj8tNm4gPply3HCArwd5j4VF590ltahftV6l/jibs2r7b2EOJdgX096tAy2LSeSbDc8tM8LC5lxdU8mVrFXraZYe6gAxry9nIRXLyHlbC5NA0q/AM/OszBl9gbb4yvOi6RTRCCvzy99uvuBpExuHtC20vMwY5oH8fdDw7jp03V8tDSeUD8vbh/SDg83RUGh5vDpLJbvTeKrtYcA+OyW88nJt+Dl7oabm7L1iB49k13u/FvrvNTJ/aOqbSmivm1DWLEvmTHdmjMn9gj5Fs2dX220Pe/l7kZuQSEbD51xeN01M401f637XtQ5/JxrQR48eJDhAwYQ1aIFXXr1Ijgigva+vnhkGEl6AhAeHIy/v3+1/F7H04qGQof4Gce7VRNzeP/CXYkOr3ln0T4AW+/01qOpRDWrWntizXilZObx0+ZjXNWnaP7wkdNZfLg0nodGdyIs0JvNh8+waPcpmvh58vbfRhvyLIVc9eEqvr6jPzd8so5tRx0HK42MCa/SnOHirPNRB0Q3Ze49A0pUOxdCCCGgij2f4tzOZObZqs1+svKg7W51dp6F37cd557/brRVB40/dVbuEIsGzdoD0qOUYc+Pzd3Gc7/uBCA1K4/McpamOJmWw33fbCJq2h98uSahWtp35HQWWXkFLNh5kpf+2FVi7tw7f++j74t/s+nwmVJfX7zX6h8XtOGeYdGMiAnHw03ZKi93iwzC38sdH083po7oWKW2dggPYN7/DQEg9tBpMnILKCjUtmUubvpsvUOC7+PpbhvO2dJcZqm0eaP2LIWaR3/YClCtBWz+PbEX914UzcDopsS9MA4vu3nrF7QLpX2YkXzd+Ok6AGZPOb/U97nzy9hzLtsSGRnJ6dRUbt+yhW5ffEHGO+9wd05Rb+8+INdi4YXnn+eHH35gx44d5OdXfQ6ydfmbjuEBfH/3AIf55MXXrfzT/NtZvTepN/5e7nxnVgA+mZbDlM/X8+j3W1l/8HS5/3bK2Vx2Hk+3PX587jbu+iqWjJx8vlyTwJAZS/jf+sPc/Nl6/tpxkgkfrub9Jft58Y/dDu+z9Wga3Z+dz7ajafQ0h+42C/Bm+rgYXr+2V6XiURF924ZKtXEhhBClkp7PapZXUMjJ9BxuGRjF8r1JHEjOJCUzj+3H0pjyeVHvyZ87/uKd68/jYHKmbVkLIRqiB0Z1JDosgIs6hzHQnHv42S39mLvxGH9sP8Hs1QkMiG7KXV9tJDLYh9XTR5b5Xt9tOMIf24yiOc/8shNLoWbKoJLrYVaUpVAzZMaSEtvfuLYXGTn5PP/bLt76ey8A6w+epk+x+YepWXm8udDo4Xz60q6M7d7cluR9dsv5trl8v00dTOfmgeQWWMgtKKRZGb2oFdHEz4vxPZqz63g6g814Doxuio+nOz9tNpZYtq6zaq9ViC9KwaK4U7QP86driyA8SkkAftp8jKNmgurjWX0JQnigD4+NLZpnufelcby3aB+FGv5vVEfWHUjhuo/XAjCkYzPbMjTFrY5P4Zctxx0qBNvz9vbm0jFjyPz1V6YC5DoWYxoMzEhNJe6FF/jaz4+/srJ44umneeqZZ6rUw3fsTDYeboq/HhiKe7F5m0E+RYnoC1d2p0uLINY/MZL7v93MqfRchncOJzzIh9XxKTzw3RbahvqxxByC/P3Gozw5vgt3mFMuSvPpyoMAjOoSTutQPz5flcD8nYnM37nAtk+zAG92nUjn7v8aPccXtAtl/cHTtAj2YfHDF5GRk8+oN5eRnlPAwGijrkBqdr5Tx6gQQghRVZJ8VqMzmXn0f2URYAxHfGxsDHf/dyPbj6bZLnDtzfhrD7kFhdLzKRq0QB9P/mHO81s1bQRN/b3w8XRncIcwUrPzWLU/hbvMIZXH0849H3HfKcc5mM//tqtKyefO42mEBXhztpSe1guiQrmsVwu8Pdx5/reiedmfrTzIpAva2Aq8AHy97jDzdxpDKu0TTytrr6O1EIyXhxtVLxdWJKZ5EPO2F02pjw4P4Mb+bWni54mfl3upRXp8PN2JDgvgt63H+W2rMfR/74vj8PIoSjDzCgp55Puttsc1vSTRP0cW9QBf2L4pu/81lryCwhLVqH+dOghLoaZ1qB8Xv7WcuRuPlpl8Aky48UY+XbKEuzJKztkNAG4CsFhYmJFBbGgo99x3H+2mz+P2we14bGwMyWdziWxSsaJsx1OzaR7sUyLxBGNY7VV9WnJZz0iGxxhVvMODfPj2zgG2fZ66pAu3fRHLb1uPl3iPl+bt5q+dJ/nmjgsd1kEGSM/J58s1h7i4awQf39SPnHyLwzzjGy5sw6U9I+nTtgmj3lzGkdPZfHdnf3q3CSG3wEKgmRj7ermz7bkxpGbl2QqESeIphBCirsi4mGo0c1k8uQXGcDENRAQZJ/gpszew7WgaT47vworHhtv2P2YO54quZFVMIeqrlk18bfOXvTzc+Pr2/vz90NAKvXZNfAq/bzvBiJhwqlgYFICzuQVc+cEqBr66mMmfrrdtnz4uhsUPD2PO3QNsF/pjukXQsokvn99yPqcycun1/AISkouqwNqvuxlRyaIszrAuYQPwfyM70r9dU5RSPHtZNx4dU3YV16imfg6Piy/9YS2wFB3mT1N/L1qF1G5VbF8vd4fEc3jnMAC6tAiid5sQmgV4G72+J9LRWvPQnC0siTtV4n3GjRvH6rw8Uks8UyQZmOLry+w5c1hxxLjp8cnKg3R66k8GvrrYYSmY4rTWtukSx9NyykxUlVK8OfE8W+JZmpFdIkh49RIeHxuDpVAz45qeLH90uK2Q0MZDZ+j81F+cMQt05RUUsmTPKdYfOM3Z3AKuNpNwH093El69hC4tjDU5HwpEBm8AABpnSURBVBzdiQHRTfH2cOf7uway7omRXNi+qXEDxKfkUlPWxFMIIYSoS5J8VoOcfAu3fxHLrOWOa9gVX/rjmr6taB3qxx/3D7bNuwGIalo9hTGEqI86hAey4clRtsf2yZC9j5fHA3BJjxa8ba6j6O6mHCp8pmXls+PYuVd3SkjOJN+iGRDd1HaDp0+bJvRpG0L7YqMMPrqhLyseG87wmHBuGRgFwMVvL+dgciar9yfzv/VHAHjrul6lDmGtKUM6NqNlE1+uPC+SB0d3qvAyHdYlNb667QKmDIpi2d4kps3dZnv+dJaR4Lx2dU82Pj260kvNVLeZk/uyatoIh/mB7ZoFkJadz5r4FH7cdMyh2JNVQEAAw/r3L3ORaQ3c7uvLpNtvZ+TIkWw/ml5iH2ssikvKyKXd9HlMnLWGg8mZrD94mmYBzidu91wUzeppI7i2byvaNPXj/X/0dnjeev64dfYGpny+gdu/jMXDTXFhu1CH/b69oz+zJvd16L1sHuxDRFD1FI4SQgghapIkn9Xg05UH+Xu3Y7XD8EBvPN3dHApQhJgLdXeLDObNiefZtjetwuLuQjQkYYHevHBFN8AoolKc1ppdJ9K5vFckV/dtxeW9Ipk+zugpsh86+9CcLVz63kq+jz1S5r9lnfv25CVd6GiOKnju8m6cHxVaYl83N2VL7J67vBsPj+5EXkEhc2KP8I9PjMI4zYN8mNC77CGgNUEpxappI2xJeEX938iOfHJTPwZ3aMYDozoBxtzChORM9pzMsPWuhdST7xxvD/cSQ5kv69kCX093W/zBGIJa3ITJk/mpjIq2HyvF4datefH11wHYfSKdED9PfrlvEC9N6A5gm/eqtebpn3fwwZL9AHy01LgJsiHhDMPfWApgW7vSWZFNfG3zTqPDAnhpQnfm3T8Efy93vt1wmGd/2cHK/cm2/T+8oU+JHstgP0/GSEVzIYQQDZQkn9XgzYVF8zknXdCad64/j0kXGHPgrEOkiusQHsAlPVvg4+lW5cXHhWhIws2emcT0ouQzJ9/Cg99t4Zctx0lMz3VYu9LaSxl3MoN8SyEPfbeFReYQzI+WxZf571iTirah/ow1q8Taz+M8l7svikapogTEy8ON2beWXpW1PvLxdGdU1wiUUgT7enKXWczmojeWMubt5by32Fh+o4UTawnXtPAgH24f4jjPd+HOopt76Tn55ORbuPyKK1iYn0/x2r5xwFO+vnzzyy94e3ujtWb3yXTGdm9Or9ZNGNUlAoB1B4xqs4/P3cZXaw/x+vw9bEg47TBH1qr4fMzqoJTihgvb0jUyiJsGRpGalc8Xa4xldK7u04qNT42SZbOEEEI0OpJ8OmlJ3CmHYYTdWwZzxXktSy1OUdz7k3oT98K4mmyeEPVGczP5PJleVHToi9UJ/LT5GA98twU3BReZcwABukYaN26unbmGNxbs4Uez0isYS7KknM21LVlkFXcynRbBPnRvGYSvlzsPjurEooeH0baCQ9s93d2wjvJ96pIu7H1xHDHNS7+B1BA8dHEnh8fxSZl0bRGEn1f9rjV317BoLuocZpsXmW33d+753AKu+3gtzZo1o0/37iy0e10uMMnPjxdff52YGGNu7MRZa0jNyrf9Ha3DU1/7K47Jn65jTuxR2+uvnbmGL1Yn0LKJL7Mm97Vtf2J82fNsq8PFXSPwdFd0NodN92wVXOa6s0IIIURDVr+vQOq5nPyixeenDu/ArhPpXNy15J3q2VPOJ6iUnpfqWNhbiIaiebBj8pmYnsMbC/bYnu8UEehQ2KVFkFFh1FKombXMmA83dXgH3N0U7ywy1uac2K8VM64x1incfPgMEz5cDUDvNkbBHjc3VeVq0tY5oA2Zt4c7Xu5u5NkV13l3UuWG8taFAG8PZk+5gMJCTcwzf5VYa3XrkVSy8gqYcNNN/Lh7N5dnG/2fT3l60nbQIO685x4AcgssbEgw1m+1L+LUPsyfA0mZJGWUHAKenW+hc/NALu4aweKHh9GumX+Nf1f3bhNiuxG5cn8yA8tYhkYIIYRo6CT5dMILvxct0zCqawSPjOlc6n4XdS67EqIQrqJZgDfubopEc7mVI6ezyLc4jhqw5+am2PrsxXR/dr5tW5cWQXSMCOCdRcbw0Z3HiwrJHEgqqlKbmlX1OXoLHxyKhlotMFSTOkYEsPN4OjOu6cnCXYlEhzWcAmduboo2oX7M3XiUy3tF2npCAZ7/dRdTr7qKf02bRgGwFPja359bbnmW3IJCfDzd+WbdYQDuH9GBXnbJ57z7h+CmFF4ebmTk5KMBreGmz9az9Ugqr1zVA6VUiQJVNck6WmZYp7By9hRCCCEaLkk+K2De9hMsjjvFG9f2sm07nJLF1+aFjZe7G11aVMfqfkI0XtZezPeX7Oeh0Z1KFJHpFllyeGuAtwdvXNuLj5buJz4pk7ZN/YgOCyCqqR8JKVk0sVu2w9q7d+ugdlx+XmSV22mtGNtYfD7lfDYfTmVMt+ZM7Ne6rptTaV7ubqRk5nHpeysdtu9bs4XWi9fSLjeXn4AHgX+26sqfy3YTsy3V1rvZt20IU0d0dHitdTkgwGFZki+nXEBGbr5UjhVCCCFqiCSf5bAUau79ehMAM67uaSsOdDDF6GX54e4B9CuliqYQomybj5whPduoYjuxXyvmxB4ttRotGEsUXd2nJcfTcmyVUZc+Opwpn68n6WwuX6xOIDE9h8zcAtzdFI+N7eyQXLi68ECfBl0d9fkrujH1m00OharuOBvHg7OepEBbmKA1k4GpwCO71vF/cRu598rpLKUfYKw9W1oRodIE+3k6rEMqhBBCiOolyWc5ttutKZiRU0CwnydpWflsPWIsby4LdwtRcXcNbc+s5QeYvfoQe06m4+6meGJ8F+4cGk2H8LKHOCqlSizJ0bapP0v2JLHj2E7btnHdm0vi2cicHxXKuidGsTcxgx82HmXLko08/unTeBQYyegkYDPwEuBZaMGz0MKnf7zGxbe8T3xQBON7NNzEWwghhGhsJPk8h/iks1z5wSrb4xnz47hpQBSXvbfSNsSvidwlF6LCpo/vwvydJ/lt63GCfT25f0RHmvh5Vekmzm2D2zEn9ghZeRZGdQknLTufqSM61ECrRX3QKSKQJ8Z3gd/fQ1uK1n5tB3xfbF/3ggIWuW1Cv/KeFHYTQggh6hGltS5/Lyf069dPx8bG1ui/UVNu+GQtq/anOGzr2SqYbUeLekMPvjJeLm6EqISDyZmkZefTo2VwhZYkOpe0rHxOZeQ0unma4hyCgiAjo2L7paWVv58QQgghqkOFLuqk5/Mcjqfm0LdtCB3DA/h2wxEAh8QTZLkUISqrXbPqq7Yqc/Rc0Nmz1bufEEIIIWpN41hLoIYkn82lR8tgpgxqV+rz9w2PruUWCSGEiwuo4PInFd1PCCGEELVGks8y5BUUkpFTQKi/F2GB3iWef+bSrjw6JqYOWiaEEC7sxhvBs5zebk9PmDy5dtojhBBCiAqT5LMMpzPzAGga4EWovxerp41g3RMjbc/7eUlFTSGEqHUPP1yx5PPBB2unPUIIIYSoMEk+y5B81ijj39TfqMIZ2cSXiCAfru3bCoDMPEudtU0IIVxWdDT88AP4+ZVMQj09je0//GDsJ4QQQoh6RZJPO7OWxfP6/DgAjpzOAqBViJ/DPi3MtQbTsvNrt3FCCCEM48bBtm1w551GVVs3N+P/d95pbB83rq5bKIQQQohSuHy125nL4vlm3WFahfiyOt5YVmXq8I4cTMkEIKpYZc5LerTg3UX7GBkTXuttFUIIYYqOhvffN/4TQgghRIPg8ut8Rk37o8S2mOaBZOVZyMqzEPvUqDpolRBCCCGEEEI0GBVaf1KG3doZ3KEZAHEnMwj08eDVq3rUcYuEEEIIIYQQonFw+WG3T13ShRf/2A1Ar9bBPH9FNyyFmk4RgXXcMiGEEEIIIYRoPFw++bx9SHsS03P4z4qDJGfkER0mC5MLIYQQQgghRHVz+eQTYPq4LjQL8ObSXpF13RQhhBBCCCGEaJQk+QTc3BR3DZM14YQQQgghhBCipkjBISGEEEIIIYQQNU6STyGEEEIIIYQQNU6STyGEEEIIIYQQNU6STyGEEEIIIYQQNa5CyadSKkIptcL82VMp9ZtSapVS6taabZ4QQgghhBBCiMag3ORTKRUCfAH4m5v+CWzUWg8CrlFKBdZg+4QQQgghhBBCNAIV6fm0ANcB6ebji4A55s/LgX7FX6CUulMpFauUik1KSqqOdgohhBBCCCGEaMDKTT611ula6zS7Tf7AMfPn00BEKa/5WGvdT2vdLywsrHpaKoQQQgghhBCiwapKwaGzgK/5c0AV30MIIYQQQgghhAupSuK4ERhs/twLSKi21gghhBBCCCGEaJQ8qvCaL4B5SqkhQFdgXfU2SQghhBBCCCFEY6O01pV/kVKRGL2f84vNBy1t3yTgUNWaVyuaAcl13YgGTmLoHImf8ySGzpMYOk9i6DyJofMkhs6TGDpPYui8hhbDZK312PJ2qlLy2ZgopWK11iUq9oqKkxg6R+LnPImh8ySGzpMYOk9i6DyJofMkhs6TGDqvscZQigUJIYQQQgghhKhxknwKIYQQQgghhKhxknzCx3XdgEZAYugciZ/zJIbOkxg6T2LoPImh8ySGzpMYOk9i6LxGGUOXn/MphBBCCCGEEKLmSc+nEEIIIYQQQogaJ8mnKJdSStV1G4QQQgghhBANW6NPPpVSvnY/SxJVBdpubLbEsPIkZkIIIaqbnFuEEA1Ro00+lVLnK6XWAbOUUs+CYxIlyqeUulApNV8pNUMpdTtIDJ0lFwtVI3FznlKqrVLKq67b0ZAppQKVUo32vFkblFIXKKXCzZ8lllWglLpVKRUl5+OqUUqF1HUbGjql1HVKqTetn2VReUqp5kopD/Nnl7rGaZRf/EqpFsCHwBfAv4G7lVJXm8+51B+4qpRSHYBZwG/ARuAZpdRE87lGedxUN6VUD6XUJuB1pdS9IMl7ZSml3JRS9wNTzMfy+a0kpVQvpdRBYC7wvVIqoK7b1NAopVoppeYA7wH/keOwasxz83PAJACtdWGdNqiBMW8IrwSeBYLkOKw8pdR04CPzZ7mWqSSl1ACl1GrgA2AgkFrHTWpwzHPyLuC/wFdKKS9XuzZsrB88D2At8KXWeiswAxgFcvFfCe2BFVrr97XW32FcMDwGcsFQEUopd+Au4AfgfeB6pdSEum1VgxQM3AaMUkqFy+e3cpRSnsAjGCe5kUBL4B7zOblwrbjhwDbgVaA3cC/IxWsVnMGI38VKqV4gMawopVQnYAnwX611W631Nuv3oXyWy2cXo2Rgu/mznE8qQBnclVLTgF8wrq2bAUeBnnXbuoZFKeWPcU5+BxgNRGFcK1qvG11Co/jSV0pdpZRao5S6Tyk1EMgCvDETTqA7sFcpFVVHTaz37GI4VSnVF+Nu1iV2u+QBmUqpyLppYcOitbYAFwJ7tdYJwFPAJKVUjzptWMPTBEgCTmAkoaJyvIBWwN9a6zTgGczkUxL5SpkIJGmt44BXgKtBbsRVhnnxHwZsAFYAt4IRQ0meyqe13gssxxiJhFLqJqVUH/M5+SxXXHugtVLqQuBypVS0K130V4U2WIDVQEut9UyllB9wDMit29Y1OFmAD7DT/Ny+iTmyy4yxS2jwyadSqiXwAPAWcBJ4G1DAPOAGs2u7FZANLDETK2GnWAxPYAxJ2QucVkp9ag4ZvRzjDldKnTW0HlNKhSulnrAml+bdrUVAE6WUu9Z6ObADmKCUalqXba2v7GLY3W6zxjjhrQN6KqXOM/eVi9VSFD8OTc8B68yY7QF2KKUi6qSBDUAZMXwNo9cJoB+QZN7oFKUo/llWSrmZF1rZQHOM5NNDKTUCjItb+Uw7KuM4/Ah4RSm1F7gTYwj4DCVzuUso5XxiTTCPAOMxep8eBf6DjAYplV0MewJorZdrrfPNz3MWEANEm/s2+HyiJpRyHPphnEuuV0oFAZHAVqXUQFf6HDfIg0WZE3RNfkAIxp39ucCPwAyt9c8Yw0TXAGO11jOBr4AnzPdw6S+ZcmL4E8YF643mc0OB48Ah4LzabWmD0RW4HxgCoLXOxOixaw+0Mff5HKM3NLouGtgAdMMuhgBa6wSt9TMYd/wPADeY2+VOf+lKOw43aK1zzJhFAB211ol12Mb6ziGGpo1a673mnMUQjCG4c5RS15hDm4Ujh8+y2bvphnEj+IDWehXwOzBVKfUfpVQL+UyXYD0OB9ttOwXkAx9qrQdjnKOHYgzfE46KH4MF5vaWgCfwIsb55H2MYeCt5RgswRrDQdYNxa6dfwIGgIwCOQdrDIeC7Zz8OxCAcV1zJfA3xqikO8yEtNFrcMmnUuoRIFYp9YhSagCQiXEh0ApAa/0qEKmUugLogzHszLrcShwQopTyc+UvmQrE8BWME18HrfUk4BaMAk6JwP46aXQ9Uyx5B+Pu1UGgjVLKOtx7LsbFfj+lVIDW+oi5z9Taa2n9VUoMW2DEp61Sari5jxuA1vokRm9Jc6XUePvnXFk5x6G1VynL7vlCjFEN1te79E04qFgMgRwArfUJrfWdWuuXgJeBG7XW+bXX2vqpIp9l8+I0CUhXRoXMG4ExQKDW+oSrf57PcRy2VUqNNLftBb4GfjBH1OwG1gN3115L66eKHIOmtRjTihK11oeAXRif79a10tB6rKIxtEs0CzELDrn659fqHDFsY/0ca60PY1wH7gKu1lp/jVHgczTGlMFGr0EdLEqpthjDP+/EmOj8MsYwHk+MIXnWO9AfYQwjnYfRU/eOUupF4F2M3r2s4u/tKioRw/cx7sRg9prsBYIwhpy5tGLJ+zBzcwZGcSENDFZKBZtzPf8G+gKTzf2OYQxndumL/jJimE5RDC9SSgWaPSbW4VIbgC3AlUopf1e/01qB43CoUirQ3Nf6Xd8eIwFAKfU48LAy5u64pIrG0K6wi68ypilg7uNvDrF3WRWI4TDrcYgxdWMwsAkowKh6a1FKtXXlz3MFYjhEKRWktU7BSD4T7eaH7QKSXfniv4LHoLVHKQmjx+kK8/E+oC3GtC2XVdHPsTlE3npO3gP8A6TnEyr8ObZ+F0ZhdPxYr6lPAZ1oYHlZVdX7X1IpFaOUekUZS6WEYPTOxWqtv8W4EL0e+BPji6QtgNb6FyAcowz0FIw/6lDgfq31y7X/W9StKsbwV8BLKXWD+R4tMXqedtbBr1BvFEvejwAvmYnmb1rrfwMrMXo7LzZf8j3G0JR/KqU+x+hFXuPiPe9lxfB3uxiGY8bQepFlXnitw6iAO6y093YVlT0O7S4MzgdilFIbMYrozHPVm3GViOFoc38FdAC+Vkq9Zj6/CqOAhEuqRAzHmC9ZYW4bp7W+GViMcZM4u9YbX09U9jjEmLs4XSn1mFLqLuBhYIGrXvxX4Zy8EfgVuEsp9TLGNc1RjATeJW8KV+F8Yj0nLwOylbkOvCurwnfhfowe9+lKqZkYI+VWAGm13vg6oOrzNbBSahzGH+RbYCzwJcZ8h/la65XKmH/zGvAJRvXBRIyLgZUYF/2faa1/r4u21xdOxnAO8IWZiLospVQMcDMQC8RjzCvuYPbKvY5xZ+sjrXWSMtZQfBAjQXrPHNaDUqo1RtIfoLVeWBe/R11yIobvaK2PmEPMLEopHyDcHLbiUpyNofker2DcALlPa/1jHfwadcqJGL6rtT6slPLGmOPUH0gwb+C5FCdi+IHW+mCx93JzxaTJ2XOKUmooxrSiCcDH5rA9l1FN5+QeGMv+ZJq1LlxKNZyT3TCWNfwHsFVrvblOfpE65EQM39daJyilojE6ycYDv7jS+aS+93yOAN7SWt+KMWzxBoylFyLNYXcnMBKl64B/Y6zf9CXG8NqOyPxEcC6GnTCGVbgsM3nfhHHH6j2MXuKvMb4wwIhZR+ACpZSn1vosRpVbL4rucKG1PqK1XuOiiaczMRwHDndac1w08XQ6hqYPtdYtXDTxrI7jMFdrvVRr/aorXShYORnD0XbvY53L7YqJZ3Uch8u11m9rrYe5YOLpTPzGWt9Ha71da/2liyae1XEMFmqt87TWs1008XT62lBrHa+1/kprPcnVzif1PfncBaxXSimt9SLzcQTG3aruAFrrWRhd3ZFa648xeu9WADdrY002V+dsDF06+aT85P0ksBTji6cQQGu9GmNu5/lKqTalvqtrkRg6z9kYWofTH6mDttcXzsSwnxyHQDV9ll0x6bTjTAz7ynEon+NqIOdk58lx6IT6Puw2Ajijtc5TSjUDPsNYKuVKjEVaF2J0d88B3jSTK2FHYugcpdQU4DTwq9ZaK6XmY4zJjwd+1lqvM/c7BEwyv1ysw2xd/WIfkBhWB4mh8ySGzpMYOk9i6ByJn/Mkhs6TGDqneEngekXbrUWntU5WRtEbd4z5ieMxhoeuAJoC2+ukkfWcxNBp8zCSd20m77nAvzCS98vMOYixwA6MZB6QL5ZiJIbOkxg6T2LoPImh8ySGzpH4OU9i6DyJoRPqdfJpTynVDmiitd5qPl4M7AaaAZu01qfqsn0NgcSw8iqZvO+ok0bWcxJD50kMnScxdJ7E0HkSQ+dI/JwnMXSexNA5DSb5BBSwRik1BngVo5TxTVrr1LptVoMiMXSCJO/Okxg6T2LoPImh8ySGzpMYOkfi5zyJofMkhpXXkJLPnhglnQdglHp+t47b0xBJDJ0jybvzJIbOkxg6T2LoPImh8ySGzpH4OU9i6DyJYSXV64JD9pRS3YBLgbe11rl13Z6GSGLoHKXUlRjrOB1EkvcqkRg6T2LoPImh8ySGzpMYOkfi5zyJofMkhpXXYJJPIeqaJO/Okxg6T2LoPImh8ySGzpMYOkfi5zyJofMkhpUnyacQQgghhBBCiBrnVtcNEEIIIYQQQgjR+EnyKYQQQgghhBCixknyKYQQQgghhBCixknyKYQQQgghhBCixknyKYQQQgghhBCixknyKYQQQgghhBCixknyKYQQQgghhBCixv0/qpDmwFt33VcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#贵州茅台买入持有策略回测可视化\n",
    "plot_max_drawdown(df,'中国平安')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "推荐几个Python量化回测框架（开源平台）：  \n",
    "聚宽 （量化回测平台）、优矿（通联量化实验室）、万矿（Wind旗下）  \n",
    "Zipline - 一个Python的回测框架   \n",
    "vnpy - 基于python的开源交易平台开发框架  \n",
    "pyalgotrade - 一个Python的事件驱动回测框架"
   ]
  }
 ],
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  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
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}
